Recession Indicators

## Warning: package 'Quandl' was built under R version 4.1.3

Introduction

For one of my machine learning classes we had a project that consumed financial data. I have extended that project to use machine learning to see if an indicator, or predictor, can be found that identifies market tops that occur prior to recessions. Then I use the model to build a trading strategy and backtest it to see how it performs.

Get Economic and Financial Data

Acquiring the data consists of two steps. First the code pulls the data into zoo objects which are then collapsed into a single data frame (df.data). Features are extracted from these series and added to the df.data data frame.

Sample call to pull economic data

Data is pulled from several sources include FRED, yahoo, and Google. The code below shows an example that pulls in the consumer price index (CPI) from the FRED. I pull data using quantmod, Quandl, and some manual extractions stored in spreadsheets.

# Consumer Price Index for All Urban Consumers: All Items
if (bRefresh == TRUE) {
  getSymbols("CPIAUCSL", src = "FRED", auto.assign = TRUE)
}

## [1] "CPIAUCSL"

## [1] "CPIAUCSL"
## [1] "USREC"
## [1] "UNRATE"
## [1] "PCEPI"
## [1] "CCSA"
## [1] "CCNSA"
## [1] "NPPTTL"
## [1] "CEU0500000001"
## [1] "U6RATE"
## [1] "PAYNSA"
## [1] "TABSHNO"
## [1] "HNONWPDPI"
## [1] "INDPRO"
## [1] "RRSFS"
## [1] "RSALES"
## [1] "W875RX1"
## [1] "RPI"
## [1] "PCOPPUSDM"
## [1] "NOBL"
## [1] "SCHD"
## [1] "PFF"
## [1] "HPI"
## [1] "GSFTX"
## [1] "LFMIX"
## [1] "LFMCX"
## [1] "LFMAX"
## [1] "LCSIX"
## [1] "BSV"
## [1] "VBIRX"
## [1] "BIV"
## [1] "VFSUX"
## [1] "LTUIX"
## [1] "PTTPX"
## [1] "NERYX"
## [1] "STIGX"
## [1] "HLGAX"
## [1] "FTRGX"
## [1] "THIIX"
## [1] "PTTRX"
## [1] "BFIGX"
## [1] "VTWO"
## [1] "EIFAX"
## [1] "ASDAX"

## Warning: ASDAX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "TRBUX"
## [1] "PRVIX"
## [1] "PRWCX"
## [1] "ADOZX"
## [1] "MERFX"
## [1] "CMNIX"
## [1] "CIHEX"
## [1] "IMPCH"
## [1] "EXPCH"
## [1] "IMPMX"
## [1] "EXPMX"
## [1] "HSN1FNSA"
## [1] "HNFSUSNSA"
## [1] "BUSLOANS"
## [1] "TOTCI"
## [1] "BUSLOANSNSA"
## [1] "REALLNNSA"
## [1] "REALLN"
## [1] "RELACBW027NBOG"
## [1] "RELACBW027SBOG"
## [1] "RREACBM027NBOG"
## [1] "RREACBM027SBOG"
## [1] "RREACBW027SBOG"
## [1] "RREACBW027NBOG"
## [1] "MORTGAGE30US"
## [1] "CONSUMERNSA"
## [1] "TOTLLNSA"
## [1] "DPSACBW027SBOG"
## [1] "DRCLACBS"
## [1] "TOTCINSA"
## [1] "SRPSABSNNCB"
## [1] "ASTLL"
## [1] "FBDILNECA"
## [1] "ASOLAL"
## [1] "ASTMA"
## [1] "ASHMA"
## [1] "ASMRMA"
## [1] "ASCMA"
## [1] "ASFMA"
## [1] "CCLBSHNO"
## [1] "FBDSILQ027S"
## [1] "FBLL"
## [1] "NCBDBIQ027S"
## [1] "DGS10"
## [1] "^TNX"

## Warning: ^TNX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## Warning: CL=F contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "DGS30"
## [1] "DGS1"
## [1] "DGS2"
## [1] "TB3MS"
## [1] "DTB3"
## [1] "^IRX"

## Warning: ^IRX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "DCOILWTICO"
## [1] "DCOILBRENTEU"
## [1] "NEWORDER"
## [1] "ALTSALES"
## [1] "ICSA"
## [1] "^GSPC"
## [1] "FXAIX"
## [1] "FTIHX"
## [1] "MDIZX"
## [1] "DODIX"
## [1] "^RLG"

## Warning: ^RLG contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "^DJI"
## [1] "^STOXX50E"

## Warning: ^STOXX50E contains missing values. Some functions will not work if
## objects contain missing values in the middle of the series. Consider using
## na.omit(), na.approx(), na.fill(), etc to remove or replace them.

## [1] "EFA"
## [1] "GDP"
## [1] "FNDEFX"
## [1] "FDEFX"
## [1] "GDPNOW"
## [1] "GDPC1"
## [1] "GDPDEF"
## [1] "VIG"
## [1] "WLRRAL"
## [1] "FEDFUNDS"
## [1] "GPDI"
## [1] "W790RC1Q027SBEA"
## [1] "MZMV"
## [1] "M1"
## [1] "M2"
## [1] "OPHNFB"
## [1] "IPMAN"
## [1] "IWD"
## [1] "GS5"
## [1] "PSAVERT"
## [1] "VIXCLS"
## [1] "VXX"
## [1] "HOUST1F"
## [1] "GFDEBTN"
## [1] "HOUST"
## [1] "HOUSTNSA"
## [1] "EXHOSLUSM495S"
## [1] "MSPUS"
## [1] "UMDMNO"
## [1] "DGORDER"
## [1] "CSUSHPINSA"
## [1] "GFDEGDQ188S"
## [1] "FYFSD"
## [1] "FYFSGDA188S"
## [1] "GDX"
## [1] "XLE"
## [1] "GSG"
## [1] "WALCL"
## [1] "OUTMS"
## [1] "MANEMP"
## [1] "PRS30006163"
## [1] "BAMLC0A3CA"
## [1] "AAA"
## [1] "SOFR"
## [1] "SOFRVOL"
## [1] "SOFR99"
## [1] "SOFR75"
## [1] "SOFR25"
## [1] "SOFR1"
## [1] "OBFR"
## [1] "OBFR99"
## [1] "OBFR75"
## [1] "OBFR25"
## [1] "OBFR1"
## [1] "RPONTSYD"
## [1] "IOER"
## [1] "WRESBAL"
## [1] "EXCSRESNW"
## [1] "ECBASSETS"
## [1] "EUNNGDP"
## [1] "CEU0600000007"
## [1] "CURRENCY"
## [1] "WCURRNS"
## [1] "BOGMBASE"
## [1] "PRS88003193"
## [1] "PPIACO"
## [1] "PCUOMFGOMFG"
## [1] "POPTHM"
## [1] "POPTHM"
## [1] "CLF16OV"
## [1] "LNU01000000"
## [1] "LNU03000000"
## [1] "UNEMPLOY"
## [1] "RSAFS"
## [1] "FRGSHPUSM649NCIS"
## [1] "BOPGTB"
## [1] "TERMCBPER24NS"
## [1] "A065RC1A027NBEA"
## [1] "PI"
## [1] "PCE"
## [1] "A053RC1Q027SBEA"
## [1] "CPROFIT"
## [1] "SPY"
## [1] "MDY"
## [1] "EES"
## [1] "IJR"
## [1] "VGSTX"
## [1] "VFINX"
## [1] "VOE"
## [1] "VOT"
## [1] "TMFGX"

## Warning: TMFGX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "IWM"
## [1] "ONEQ"
## [1] "FSMAX"
## [1] "FXNAX"
## [1] "HAINX"
## [1] "HNACX"
## [1] "VEU"
## [1] "VEIRX"
## [1] "BIL"
## [1] "IVOO"
## [1] "VO"
## [1] "CZA"
## [1] "VYM"
## [1] "ACWI"
## [1] "SLY"

## Warning: SLY contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "QQQ"
## [1] "HYMB"
## [1] "GOLD"
## [1] "BKR"
## [1] "SLB"
## [1] "HAL"
## [1] "IP"
## [1] "PKG"
## [1] "UPS"
## [1] "FDX"
## [1] "T"
## [1] "VZ"

Load up the EIA data

Load rig count data

The Baker Hughes rig count numbers

USDA data

Loading in farm data

## Warning in read_fun(path = enc2native(normalizePath(path)), sheet_i = sheet, :
## Expecting numeric in E3 / R3C5: got a date

## New names:
## * `` -> ...1
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## * ...

## Warning: NAs introduced by coercion

Loading in Silverblatt’s S&P 500 spreadsheet starting with the quarterly data.

## New names:
## * `` -> ...2
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## * `` -> ...5
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Now load in the estimates

## New names:
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## * `` -> ...4
## * `` -> ...5
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Covid 19 Data

Get the Covid-19 data from JHU

## Rows: 919308 Columns: 15
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## chr  (8): province, country, type, iso2, iso3, combined_key, continent_name,...
## dbl  (6): lat, long, cases, uid, code3, population
## date (1): date
## 
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Downloading GitHub repo RamiKrispin/coronavirus@master

##   
  
  
v  checking for file 'C:\Users\Rainy\AppData\Local\Temp\RtmpCoTbKk\remotes2c2c2362dee\RamiKrispin-coronavirus-b286a3c/DESCRIPTION' (457ms)
## 
  
  
  
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##    checking DESCRIPTION meta-information ...
  
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## Caught an warning!

## <simpleWarning: package 'coronavirus' is in use and will not be installed>

## `summarise()` has grouped output by 'country'. You can override using the
## `.groups` argument.

## Warning: Removed 3 row(s) containing missing values (geom_path).

Feature Extraction

With the raw data downloaded, some of the interesting features can be extracted. The first step is reconcile the time intervals. Some of the data is released monthly and some daily. I chose to interpolate all data to a daily interval. The first section of code adds the daily rows to the dataframe.

The code performs interpolation for continuous data or carries it forward for binary data like the recession indicators.

source("calcInterpolate.r")
df.data <- calcInterpolate(df.symbols)

## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

Truncate data

Create aggregate series

Some analysis requires that two or more series be combined. For example, normallizing debt by GDP to get a sense of the proportion of debt to the total economy helps understand the debt cycle.

Year over year, smoothed derivative, and log trends tend to smooth out seasonal variation. It gets used so often that I do this for every series downloaded.

source("calcFeatures.r")
lst.df <- calcFeatures(df.data, df.symbols)

## [1] "USREC has zero or negative values. Log series will be zero."
## [1] "GSFTX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMIX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMCX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMAX.Volume has zero or negative values. Log series will be zero."
## [1] "LCSIX.Volume has zero or negative values. Log series will be zero."
## [1] "VBIRX.Volume has zero or negative values. Log series will be zero."
## [1] "VFSUX.Volume has zero or negative values. Log series will be zero."
## [1] "LTUIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTPX.Volume has zero or negative values. Log series will be zero."
## [1] "NERYX.Volume has zero or negative values. Log series will be zero."
## [1] "STIGX.Volume has zero or negative values. Log series will be zero."
## [1] "HLGAX.Volume has zero or negative values. Log series will be zero."
## [1] "FTRGX.Volume has zero or negative values. Log series will be zero."
## [1] "THIIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTRX.Volume has zero or negative values. Log series will be zero."
## [1] "BFIGX.Volume has zero or negative values. Log series will be zero."
## [1] "EIFAX.Volume has zero or negative values. Log series will be zero."
## [1] "ASDAX.Volume has zero or negative values. Log series will be zero."
## [1] "TRBUX.Volume has zero or negative values. Log series will be zero."
## [1] "PRVIX.Volume has zero or negative values. Log series will be zero."
## [1] "PRWCX.Volume has zero or negative values. Log series will be zero."
## [1] "ADOZX.Volume has zero or negative values. Log series will be zero."
## [1] "MERFX.Volume has zero or negative values. Log series will be zero."
## [1] "CMNIX.Volume has zero or negative values. Log series will be zero."
## [1] "CIHEX.Volume has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB has zero or negative values. Log series will be zero."
## [1] "TNX.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Open has zero or negative values. Log series will be zero."
## [1] "CLF.Low has zero or negative values. Log series will be zero."
## [1] "CLF.Close has zero or negative values. Log series will be zero."
## [1] "CLF.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Adjusted has zero or negative values. Log series will be zero."
## [1] "DTB3 has zero or negative values. Log series will be zero."
## [1] "IRX.Open has zero or negative values. Log series will be zero."
## [1] "IRX.High has zero or negative values. Log series will be zero."
## [1] "IRX.Low has zero or negative values. Log series will be zero."
## [1] "IRX.Close has zero or negative values. Log series will be zero."
## [1] "IRX.Volume has zero or negative values. Log series will be zero."
## [1] "IRX.Adjusted has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO has zero or negative values. Log series will be zero."
## [1] "FXAIX.Volume has zero or negative values. Log series will be zero."
## [1] "FTIHX.Volume has zero or negative values. Log series will be zero."
## [1] "MDIZX.Volume has zero or negative values. Log series will be zero."
## [1] "DODIX.Volume has zero or negative values. Log series will be zero."
## [1] "RLG.Volume has zero or negative values. Log series will be zero."
## [1] "STOXX50E.Volume has zero or negative values. Log series will be zero."
## [1] "GDPNOW has zero or negative values. Log series will be zero."
## [1] "W790RC1Q027SBEA has zero or negative values. Log series will be zero."
## [1] "VXX.Volume has zero or negative values. Log series will be zero."
## [1] "FYFSD has zero or negative values. Log series will be zero."
## [1] "FYFSGDA188S has zero or negative values. Log series will be zero."
## [1] "SOFR25 has zero or negative values. Log series will be zero."
## [1] "SOFR1 has zero or negative values. Log series will be zero."
## [1] "RPONTSYD has zero or negative values. Log series will be zero."
## [1] "BOPGTB has zero or negative values. Log series will be zero."
## [1] "EES.Volume has zero or negative values. Log series will be zero."
## [1] "VGSTX.Volume has zero or negative values. Log series will be zero."
## [1] "VFINX.Volume has zero or negative values. Log series will be zero."
## [1] "TMFGX.Volume has zero or negative values. Log series will be zero."
## [1] "FSMAX.Volume has zero or negative values. Log series will be zero."
## [1] "FXNAX.Volume has zero or negative values. Log series will be zero."
## [1] "HAINX.Volume has zero or negative values. Log series will be zero."
## [1] "HNACX.Volume has zero or negative values. Log series will be zero."
## [1] "VEIRX.Volume has zero or negative values. Log series will be zero."
## [1] "IVOO.Volume has zero or negative values. Log series will be zero."
## [1] "VO.Volume has zero or negative values. Log series will be zero."
## [1] "CZA.Volume has zero or negative values. Log series will be zero."
## [1] "SLY.Volume has zero or negative values. Log series will be zero."
## [1] "HYMB.Volume has zero or negative values. Log series will be zero."
## [1] "GOLD.Open has zero or negative values. Log series will be zero."
## [1] "GOLD.Volume has zero or negative values. Log series will be zero."
## [1] "BKR.Open has zero or negative values. Log series will be zero."
## [1] "BKR.Volume has zero or negative values. Log series will be zero."
## [1] "HAL.Open has zero or negative values. Log series will be zero."
## [1] "HAL.Volume has zero or negative values. Log series will be zero."
## [1] "IP.Open has zero or negative values. Log series will be zero."
## [1] "T.Open has zero or negative values. Log series will be zero."
## [1] "OPEARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "AREARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "OCCEquityVolume has zero or negative values. Log series will be zero."
## [1] "OCCNonEquityVolume has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA.by.GDP has zero or negative values. Log series will be zero."
## [1] "EXPCH.minus.IMPCH has zero or negative values. Log series will be zero."
## [1] "EXPMX.minus.IMPMX has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB.by.GDP has zero or negative values. Log series will be zero."
## [1] "DGS30TO10 has zero or negative values. Log series will be zero."
## [1] "DGS10TO1 has zero or negative values. Log series will be zero."
## [1] "DGS10TO2 has zero or negative values. Log series will be zero."
## [1] "DGS10TOTB3MS has zero or negative values. Log series will be zero."
## [1] "DGS10TODTB3 has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO.by.PPIACO has zero or negative values. Log series will be zero."
## [1] "GSPC.DailySwing has zero or negative values. Log series will be zero."

df.data <- lst.df[[1]]
df.symbols <- lst.df[[2]]

Recession calculations

Summary calculations

These values are used below

Conclusion

In this worksheet a model predicting the onset of recession was built. From the model a trading rule was derived to allow backtesting. The model performed well and the trading rule backtesting showed that applying this in the post-WWII period would have resulted in an increase in returns. That is not too bad, but there are a few changes that would likely improve the model:

• Go long on short term bonds, rather than just roll out of the market. That way at least some returns would be generated during recessions.
• Refine the recession indicator.

Market Conditions

#The model is predicting a `r paste(sprintf("%3.0f", tail(df.data$recession.initiation.smooth.avg,1)[[1]]*100), "%", sep="")` chance of recession in the next 12 months. :

#- P/E ratio of `r sprintf("%3.2f", tail(df.data$MULTPLSP500PERATIOMONTH,1))` compares to a historical mean value over the last decade of `r sprintf("%3.2f", df.data$MULTPLSP500PERATIOMONTH_Mean[1])`. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

• S&P 500 Volume, last updated on 2025-04-04, is positive over the last year and positive over the last month.

Unemployment

• Headline unemployment (U-3) stands at 4.20% (last updated on 2025-03-01) which is near the 1-year average of 4.12% and rising with respect to the low in the last twelve months of 3.90%. Unlikely the rate will drop again.

• Payrolls (BLS data, NSA) year-over-year stands at 0.57% which is above the 1-year average of 1.24% and falling with respect to the peak, in the last twelve months, of 1.45%.

• Jobless claims (ICSA data) year-over-year stands at 3.37% (last updated on 2025-03-29) which is in-line with the 1-year average of 1.94% and below the peak, in the last twelve months, of 22.83%.

## Warning: Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_hline).

Personal Income

• Real personal income year over year growth stands at 1.02% (last updated on 2025-02-01). This is below the recent peak of 2.94%.

Yield Curve and Bond Market

• The 10-year to 3-month yield stands at -0.16% (last updated on 2025-04-04). This is above the recent low of -1.31%. The trend is negative over the last year and negative over the last month.

## Warning: Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_hline).

• Auto sales flat?

Auxillary Series

I explored additional data series. The sections below have those data series along with comments.

Recent Highs

Print out the new 180 day high values

df.symbolsTrue <-
  df.symbols[df.symbols$'Max180' == TRUE, c("string.symbol", "string.description")]
df.symbolsTrue <-
  df.symbolsTrue[!(is.na(df.symbolsTrue$string.symbol)), ]
df.symbolsTrue <-
  df.symbolsTrue[!(df.symbolsTrue$string.symbol == 'USREC'), ]
#print(head(df.symbolsTrue,20))

kable(df.symbolsTrue, caption = "6-Month High") %>%
  kable_styling(bootstrap_options = c("striped", "hover"))  

6-Month High

	string.symbol	string.description
1	CPIAUCSL	Consumer Price Index for All Urban Consumers: All Items
3	UNRATE	Civilian Unemployment Rate U-3
4	PCEPI	Personal Consumption Expenditures: Chain-type Price Index
5	CCSA	Continued Claims (Insured Unemployment)
7	NPPTTL	Total Nonfarm Private Payroll Employment (ADP)
11	TABSHNO	Households and nonprofit organizations; total assets, Level
12	HNONWPDPI	Household Net Worth, percent Dispsable Income
13	INDPRO	Industrial Production Index
15	RSALES	Real Retail Sales (DISCONTINUED)
16	W875RX1	Real personal income excluding current transfer receipts
17	RPI	Real personal income
55	HSN1FNSA	New One Family Houses Sold: United States (Monthly, NSA)
61	REALLN	Real Estate Loans, All Commercial Banks (Monthly, SA)
63	RELACBW027SBOG	Real Estate Loans, All Commercial Banks (Weekly, SA)
65	RREACBM027SBOG	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
66	RREACBW027SBOG	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
71	DPSACBW027SBOG	Deposits, All Commercial Banks
72	DRCLACBS	Delinquency Rate on Consumer Loans, All Commercial Banks, SA
74	SRPSABSNNCB	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
75	ASTLL	All sectors; total loans; liability, Level (NSA)
76	FBDILNECA	Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
77	ASOLAL	All sectors; other loans and advances; liability, Level (NSA)
78	ASTMA	All sectors; total mortgages; asset, Level (NSA)
79	ASHMA	All sectors; home mortgages; asset, Level (NSA)
80	ASMRMA	All sectors; multifamily residential mortgages; asset, Level (NSA)
81	ASCMA	All sectors; commercial mortgages; asset, Level (NSA)
82	ASFMA	All sectors; farm mortgages; asset, Level (NSA)
83	CCLBSHNO	Households and nonprofit organizations; consumer credit; liability, Level (NSA)
84	FBDSILQ027S	Domestic financial sectors debt securities; liability, Level (NSA)
85	FBLL	Domestic financial sectors loans; liability, Level (NSA)
86	NCBDBIQ027S	Nonfinancial corporate business; debt securities; liability, Level
99	ALTSALES	Light Weight Vehicle Sales: Autos and Light Trucks
110	GDP	Gross Domestic Product
111	FNDEFX	Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
112	FDEFX	Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
114	GDPC1	Real Gross Domestic Product
115	GDPDEF	Gross Domestic Product: Implicit Price Deflator
119	GPDI	Gross Private Domestic Investment
120	W790RC1Q027SBEA	Net domestic investment: Private: Domestic busines
121	MZMV	Velocity of MZM Money Stock
122	M1	M1 Money Stock
123	M2	M2 Money Stock
124	OPHNFB	Nonfarm Business Sector: Real Output Per Hour of All Persons, SA
125	IPMAN	Industrial Production: Manufacturing (NAICS)
128	PSAVERT	Personal Saving Rate
129	VIXCLS	CBOE Volatility Index
131	HOUST1F	Privately Owned Housing Starts: 1-Unit Structures
132	GFDEBTN	Federal Debt: Total Public Debt
134	HOUSTNSA	Housing Starts: Total: New Privately Owned Housing Units Started, NSA
136	MSPUS	Median Sales Price of Houses Sold for the United States (NSA)
138	DGORDER	Manufacturers’ New Orders: Durable Goods (SA)
140	GFDEGDQ188S	Federal Debt: Total Public Debt as Percent of Gross Domestic Product
141	FYFSD	Federal Surplus or Deficit
142	FYFSGDA188S	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
147	OUTMS	Manufacturing Sector: Real Output
149	PRS30006163	Manufacturing Sector: Real Output Per Person
150	BAMLC0A3CA	ICE BofAML US Corporate A Option-Adjusted Spread
164	IOER	Interest Rate on Excess Reserves
166	EXCSRESNW	Excess Reserves of Depository Institutions
167	ECBASSETS	Central Bank Assets for Euro Area (11-19 Countries)
168	EUNNGDP	Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
170	CURRENCY	Currency Component of M1 (Seasonally Adjusted)
173	PRS88003193	Nonfinancial Corporations Sector: Unit Profits
174	PPIACO	Producer Price Index for All Commodities
175	PCUOMFGOMFG	Producer Price Index by Industry: Total Manufacturing Industries
176	POPTHM	Population (U.S.)
177	POPTHM	Population (U.S.)
179	LNU01000000	Civilian Labor Force Level, NSA
186	A065RC1A027NBEA	Personal income (NSA)
187	PI	Personal income (SA)
188	PCE	Personal Consumption Expenditures (SA)
189	A053RC1Q027SBEA	National income: Corporate profits before tax (without IVA and CCAdj)
190	CPROFIT	Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
227	PETA103600001M	U.S. Total Gasoline Retail Sales by Refiners, Monthly
228	PETA123600001M	U.S. Regular Gasoline Retail Sales by Refiners, Monthly
229	PETA143B00001M	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
230	PETA133B00001M	U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly
231	TOTALOGNRPUSM	Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
232	TOTALPANRPUSM	Crude Oil Rotary Rigs in Operation, Monthly
234	BKRTotal	Total Rig Count
235	BKRGas	Gas Rig Count
236	BKROil	Oil Rig Count
237	FARMINCOME	Net Farm Income
238	OPEARNINGSPERSHARE	Operating Earnings per Share
239	AREARNINGSPERSHARE	As-Reported Earnings per Share
240	CASHDIVIDENDSPERSHR	Cash Dividends per Share
241	SALESPERSHR	Sales per Share
242	BOOKVALPERSHR	Book value per Share
243	CAPEXPERSHR	Cap ex per Share
244	PRICE	Price
245	OPEARNINGSTTM	TTM Operating Earnings
246	AREARNINGSTTM	TTM Reported Earnings
247	FINRAMarginDebt	Margin Debt
248	FINRAFreeCreditMargin	Free Credit Balances in Customers’ Securities Margin Accounts
249	OCCEquityVolume	Equity Options Volume
250	OCCNonEquityVolume	Non-Equity Options Volume
262	W875RX1.by.GDP	Real Personal Income Normalized by GDP
263	A065RC1A027NBEA.by.GDP	Personal Income (NSA) Normalized by GDP
264	PI.by.GDP	Personal Income (SA) Normalized by GDP
265	A053RC1Q027SBEA.by.GDP	National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
266	CPROFIT.by.GDP	National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
269	RREACBM027SBOG.by.GDP	Residental Real Estate Loans (Monthly, SA) divided by GDP
270	RREACBW027SBOG.by.GDP	Residental Real Estate Loans (Weekly, SA) divided by GDP
273	DGORDER.by.GDP	Durable Goods (Monthly, NSA) divided by GDP
274	ASHMA.by.GDP	Home Mortgages (Quarterly, NSA) divided by GDP
284	EXCSRESNW.by.GDP	Excess Reserves of Depository Institutions Divided by GDP
287	EXPCH.minus.IMPCH	U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
289	SRPSABSNNCB.by.GDP	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
290	ASTLL.by.GDP	All sectors; total loans; liability, Level (NSA) Divided by GDP
291	ASFMA.by.GDP	All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
292	ASFMA.by.ASTLL	All sectors; total loans Divided by farm mortgages
295	FARMINCOME.by.GDP	Farm Income (Annual, NSA) Divided by GDP
298	ECBASSETS.by.EUNNGDP	Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
304	DGS10ByAAA	AAA ratio to 10 year treasury (AAA/DGS10)
311	GDP.by.GDPDEF	Nominal GDP Normalized by GDP def
313	GSG.Close.by.GSPC.Close	GSCI Commodity-Indexed Trust, Normalized by S&P 500
319	GSPC.DailySwing	S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
330	CPIAUCSL_YoY5	Consumer Price Index for All Urban Consumers: All Items 5 Year over 5 Year
333	CPIAUCSL_SmoothDer	Derivative of Smoothed Consumer Price Index for All Urban Consumers: All Items
334	CPIAUCSL_Log	Log of Consumer Price Index for All Urban Consumers: All Items
335	CPIAUCSL_mva365	Consumer Price Index for All Urban Consumers: All Items 365 Day MA
336	CPIAUCSL_mva200	Consumer Price Index for All Urban Consumers: All Items 200 Day MA
337	CPIAUCSL_mva050	Consumer Price Index for All Urban Consumers: All Items 50 Day MA
338	USREC_YoY	NBER based Recession Indicators Year over Year
339	USREC_YoY4	NBER based Recession Indicators 4 Year over 4 Year
341	USREC_Smooth	Savitsky-Golay Smoothed (p=3, n=365) NBER based Recession Indicators
342	USREC_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) NBER based Recession Indicators
343	USREC_SmoothDer	Derivative of Smoothed NBER based Recession Indicators
344	USREC_Log	Log of NBER based Recession Indicators
345	USREC_mva365	NBER based Recession Indicators 365 Day MA
346	USREC_mva200	NBER based Recession Indicators 200 Day MA
347	USREC_mva050	NBER based Recession Indicators 50 Day MA
349	UNRATE_YoY4	Civilian Unemployment Rate U-3 4 Year over 4 Year
351	UNRATE_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Civilian Unemployment Rate U-3
353	UNRATE_SmoothDer	Derivative of Smoothed Civilian Unemployment Rate U-3
354	UNRATE_Log	Log of Civilian Unemployment Rate U-3
355	UNRATE_mva365	Civilian Unemployment Rate U-3 365 Day MA
357	UNRATE_mva050	Civilian Unemployment Rate U-3 50 Day MA
361	PCEPI_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Personal Consumption Expenditures: Chain-type Price Index
363	PCEPI_SmoothDer	Derivative of Smoothed Personal Consumption Expenditures: Chain-type Price Index
364	PCEPI_Log	Log of Personal Consumption Expenditures: Chain-type Price Index
365	PCEPI_mva365	Personal Consumption Expenditures: Chain-type Price Index 365 Day MA
366	PCEPI_mva200	Personal Consumption Expenditures: Chain-type Price Index 200 Day MA
367	PCEPI_mva050	Personal Consumption Expenditures: Chain-type Price Index 50 Day MA
369	CCSA_YoY4	Continued Claims (Insured Unemployment) 4 Year over 4 Year
371	CCSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Continued Claims (Insured Unemployment)
374	CCSA_Log	Log of Continued Claims (Insured Unemployment)
375	CCSA_mva365	Continued Claims (Insured Unemployment) 365 Day MA
376	CCSA_mva200	Continued Claims (Insured Unemployment) 200 Day MA
377	CCSA_mva050	Continued Claims (Insured Unemployment) 50 Day MA
378	CCNSA_YoY	Continued Claims (Insured Unemployment, NSA) Year over Year
379	CCNSA_YoY4	Continued Claims (Insured Unemployment, NSA) 4 Year over 4 Year
381	CCNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Continued Claims (Insured Unemployment, NSA)
383	CCNSA_SmoothDer	Derivative of Smoothed Continued Claims (Insured Unemployment, NSA)
385	CCNSA_mva365	Continued Claims (Insured Unemployment, NSA) 365 Day MA
386	CCNSA_mva200	Continued Claims (Insured Unemployment, NSA) 200 Day MA
388	NPPTTL_YoY	Total Nonfarm Private Payroll Employment (ADP) Year over Year
394	NPPTTL_Log	Log of Total Nonfarm Private Payroll Employment (ADP)
395	NPPTTL_mva365	Total Nonfarm Private Payroll Employment (ADP) 365 Day MA
396	NPPTTL_mva200	Total Nonfarm Private Payroll Employment (ADP) 200 Day MA
397	NPPTTL_mva050	Total Nonfarm Private Payroll Employment (ADP) 50 Day MA
405	CEU0500000001_mva365	All Employees, Total Private (NSA) 365 Day MA
409	U6RATE_YoY4	Total unemployed + margin + part-time U-6 4 Year over 4 Year
411	U6RATE_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Total unemployed + margin + part-time U-6
413	U6RATE_SmoothDer	Derivative of Smoothed Total unemployed + margin + part-time U-6
415	U6RATE_mva365	Total unemployed + margin + part-time U-6 365 Day MA
416	U6RATE_mva200	Total unemployed + margin + part-time U-6 200 Day MA
425	PAYNSA_mva365	All Employees: Total Nonfarm Payrolls (NSA) 365 Day MA
431	TABSHNO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Households and nonprofit organizations; total assets, Level
434	TABSHNO_Log	Log of Households and nonprofit organizations; total assets, Level
435	TABSHNO_mva365	Households and nonprofit organizations; total assets, Level 365 Day MA
436	TABSHNO_mva200	Households and nonprofit organizations; total assets, Level 200 Day MA
437	TABSHNO_mva050	Households and nonprofit organizations; total assets, Level 50 Day MA
441	HNONWPDPI_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Household Net Worth, percent Dispsable Income
444	HNONWPDPI_Log	Log of Household Net Worth, percent Dispsable Income
445	HNONWPDPI_mva365	Household Net Worth, percent Dispsable Income 365 Day MA
451	INDPRO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Industrial Production Index
453	INDPRO_SmoothDer	Derivative of Smoothed Industrial Production Index
454	INDPRO_Log	Log of Industrial Production Index
455	INDPRO_mva365	Industrial Production Index 365 Day MA
456	INDPRO_mva200	Industrial Production Index 200 Day MA
457	INDPRO_mva050	Industrial Production Index 50 Day MA
465	RRSFS_mva365	Real Retail and Food Services Sales 365 Day MA
468	RSALES_YoY	Real Retail Sales (DISCONTINUED) Year over Year
469	RSALES_YoY4	Real Retail Sales (DISCONTINUED) 4 Year over 4 Year
470	RSALES_YoY5	Real Retail Sales (DISCONTINUED) 5 Year over 5 Year
474	RSALES_Log	Log of Real Retail Sales (DISCONTINUED)
475	RSALES_mva365	Real Retail Sales (DISCONTINUED) 365 Day MA
476	RSALES_mva200	Real Retail Sales (DISCONTINUED) 200 Day MA
477	RSALES_mva050	Real Retail Sales (DISCONTINUED) 50 Day MA
483	W875RX1_SmoothDer	Derivative of Smoothed Real personal income excluding current transfer receipts
484	W875RX1_Log	Log of Real personal income excluding current transfer receipts
485	W875RX1_mva365	Real personal income excluding current transfer receipts 365 Day MA
486	W875RX1_mva200	Real personal income excluding current transfer receipts 200 Day MA
487	W875RX1_mva050	Real personal income excluding current transfer receipts 50 Day MA
491	RPI_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real personal income
493	RPI_SmoothDer	Derivative of Smoothed Real personal income
494	RPI_Log	Log of Real personal income
495	RPI_mva365	Real personal income 365 Day MA
496	RPI_mva200	Real personal income 200 Day MA
497	RPI_mva050	Real personal income 50 Day MA
501	PCOPPUSDM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Global price of Copper
503	PCOPPUSDM_SmoothDer	Derivative of Smoothed Global price of Copper
549	NOBL.Volume_YoY4	4 Year over 4 Year
551	NOBL.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
552	NOBL.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
553	NOBL.Volume_SmoothDer	Derivative of Smoothed
554	NOBL.Volume_Log	Log of
555	NOBL.Volume_mva365	365 Day MA
556	NOBL.Volume_mva200	200 Day MA
557	NOBL.Volume_mva050	50 Day MA
608	SCHD.Volume_YoY	Year over Year
611	SCHD.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
612	SCHD.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
613	SCHD.Volume_SmoothDer	Derivative of Smoothed
614	SCHD.Volume_Log	Log of
615	SCHD.Volume_mva365	365 Day MA
616	SCHD.Volume_mva200	200 Day MA
617	SCHD.Volume_mva050	50 Day MA
668	PFF.Volume_YoY	Year over Year
669	PFF.Volume_YoY4	4 Year over 4 Year
672	PFF.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
673	PFF.Volume_SmoothDer	Derivative of Smoothed
674	PFF.Volume_Log	Log of
676	PFF.Volume_mva200	200 Day MA
729	HPI.Volume_YoY4	4 Year over 4 Year
732	HPI.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
734	HPI.Volume_Log	Log of
745	HPI.Adjusted_mva365	365 Day MA
788	GSFTX.Volume_YoY	Year over Year
789	GSFTX.Volume_YoY4	4 Year over 4 Year
790	GSFTX.Volume_YoY5	5 Year over 5 Year
791	GSFTX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
792	GSFTX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
793	GSFTX.Volume_SmoothDer	Derivative of Smoothed
794	GSFTX.Volume_Log	Log of
795	GSFTX.Volume_mva365	365 Day MA
796	GSFTX.Volume_mva200	200 Day MA
797	GSFTX.Volume_mva050	50 Day MA
805	GSFTX.Adjusted_mva365	365 Day MA
813	LFMIX.Open_SmoothDer	Derivative of Smoothed
823	LFMIX.High_SmoothDer	Derivative of Smoothed
833	LFMIX.Low_SmoothDer	Derivative of Smoothed
843	LFMIX.Close_SmoothDer	Derivative of Smoothed
848	LFMIX.Volume_YoY	Year over Year
849	LFMIX.Volume_YoY4	4 Year over 4 Year
850	LFMIX.Volume_YoY5	5 Year over 5 Year
851	LFMIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
852	LFMIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
853	LFMIX.Volume_SmoothDer	Derivative of Smoothed
854	LFMIX.Volume_Log	Log of
855	LFMIX.Volume_mva365	365 Day MA
856	LFMIX.Volume_mva200	200 Day MA
857	LFMIX.Volume_mva050	50 Day MA
861	LFMIX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
863	LFMIX.Adjusted_SmoothDer	Derivative of Smoothed
873	LFMCX.Open_SmoothDer	Derivative of Smoothed
883	LFMCX.High_SmoothDer	Derivative of Smoothed
893	LFMCX.Low_SmoothDer	Derivative of Smoothed
903	LFMCX.Close_SmoothDer	Derivative of Smoothed
908	LFMCX.Volume_YoY	Year over Year
909	LFMCX.Volume_YoY4	4 Year over 4 Year
910	LFMCX.Volume_YoY5	5 Year over 5 Year
911	LFMCX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
912	LFMCX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
913	LFMCX.Volume_SmoothDer	Derivative of Smoothed
914	LFMCX.Volume_Log	Log of
915	LFMCX.Volume_mva365	365 Day MA
916	LFMCX.Volume_mva200	200 Day MA
917	LFMCX.Volume_mva050	50 Day MA
921	LFMCX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
923	LFMCX.Adjusted_SmoothDer	Derivative of Smoothed
933	LFMAX.Open_SmoothDer	Derivative of Smoothed
943	LFMAX.High_SmoothDer	Derivative of Smoothed
953	LFMAX.Low_SmoothDer	Derivative of Smoothed
963	LFMAX.Close_SmoothDer	Derivative of Smoothed
968	LFMAX.Volume_YoY	Year over Year
969	LFMAX.Volume_YoY4	4 Year over 4 Year
970	LFMAX.Volume_YoY5	5 Year over 5 Year
971	LFMAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
972	LFMAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
973	LFMAX.Volume_SmoothDer	Derivative of Smoothed
974	LFMAX.Volume_Log	Log of
975	LFMAX.Volume_mva365	365 Day MA
976	LFMAX.Volume_mva200	200 Day MA
977	LFMAX.Volume_mva050	50 Day MA
981	LFMAX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
983	LFMAX.Adjusted_SmoothDer	Derivative of Smoothed
993	LCSIX.Open_SmoothDer	Derivative of Smoothed
1003	LCSIX.High_SmoothDer	Derivative of Smoothed
1013	LCSIX.Low_SmoothDer	Derivative of Smoothed
1023	LCSIX.Close_SmoothDer	Derivative of Smoothed
1028	LCSIX.Volume_YoY	Year over Year
1029	LCSIX.Volume_YoY4	4 Year over 4 Year
1030	LCSIX.Volume_YoY5	5 Year over 5 Year
1031	LCSIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1032	LCSIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1033	LCSIX.Volume_SmoothDer	Derivative of Smoothed
1034	LCSIX.Volume_Log	Log of
1035	LCSIX.Volume_mva365	365 Day MA
1036	LCSIX.Volume_mva200	200 Day MA
1037	LCSIX.Volume_mva050	50 Day MA
1043	LCSIX.Adjusted_SmoothDer	Derivative of Smoothed
1051	BSV.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1052	BSV.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1054	BSV.Open_Log	Log of
1055	BSV.Open_mva365	365 Day MA
1061	BSV.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1062	BSV.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1064	BSV.High_Log	Log of
1065	BSV.High_mva365	365 Day MA
1071	BSV.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1072	BSV.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1074	BSV.Low_Log	Log of
1075	BSV.Low_mva365	365 Day MA
1081	BSV.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1082	BSV.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1084	BSV.Close_Log	Log of
1085	BSV.Close_mva365	365 Day MA
1096	BSV.Volume_mva200	200 Day MA
1101	BSV.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1102	BSV.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1104	BSV.Adjusted_Log	Log of
1105	BSV.Adjusted_mva365	365 Day MA
1106	BSV.Adjusted_mva200	200 Day MA
1107	BSV.Adjusted_mva050	50 Day MA
1111	VBIRX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1112	VBIRX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1114	VBIRX.Open_Log	Log of
1115	VBIRX.Open_mva365	365 Day MA
1121	VBIRX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1122	VBIRX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1124	VBIRX.High_Log	Log of
1125	VBIRX.High_mva365	365 Day MA
1131	VBIRX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1132	VBIRX.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1134	VBIRX.Low_Log	Log of
1135	VBIRX.Low_mva365	365 Day MA
1141	VBIRX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1142	VBIRX.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1144	VBIRX.Close_Log	Log of
1145	VBIRX.Close_mva365	365 Day MA
1148	VBIRX.Volume_YoY	Year over Year
1149	VBIRX.Volume_YoY4	4 Year over 4 Year
1150	VBIRX.Volume_YoY5	5 Year over 5 Year
1151	VBIRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1152	VBIRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1153	VBIRX.Volume_SmoothDer	Derivative of Smoothed
1154	VBIRX.Volume_Log	Log of
1155	VBIRX.Volume_mva365	365 Day MA
1156	VBIRX.Volume_mva200	200 Day MA
1157	VBIRX.Volume_mva050	50 Day MA
1161	VBIRX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1162	VBIRX.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1164	VBIRX.Adjusted_Log	Log of
1165	VBIRX.Adjusted_mva365	365 Day MA
1166	VBIRX.Adjusted_mva200	200 Day MA
1167	VBIRX.Adjusted_mva050	50 Day MA
1172	BIV.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1174	BIV.Open_Log	Log of
1182	BIV.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1184	BIV.High_Log	Log of
1192	BIV.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1202	BIV.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1212	BIV.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1216	BIV.Volume_mva200	200 Day MA
1221	BIV.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1222	BIV.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1224	BIV.Adjusted_Log	Log of
1225	BIV.Adjusted_mva365	365 Day MA
1231	VFSUX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1235	VFSUX.Open_mva365	365 Day MA
1241	VFSUX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1245	VFSUX.High_mva365	365 Day MA
1251	VFSUX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1255	VFSUX.Low_mva365	365 Day MA
1261	VFSUX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1265	VFSUX.Close_mva365	365 Day MA
1268	VFSUX.Volume_YoY	Year over Year
1269	VFSUX.Volume_YoY4	4 Year over 4 Year
1270	VFSUX.Volume_YoY5	5 Year over 5 Year
1271	VFSUX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1272	VFSUX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1273	VFSUX.Volume_SmoothDer	Derivative of Smoothed
1274	VFSUX.Volume_Log	Log of
1275	VFSUX.Volume_mva365	365 Day MA
1276	VFSUX.Volume_mva200	200 Day MA
1277	VFSUX.Volume_mva050	50 Day MA
1281	VFSUX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1285	VFSUX.Adjusted_mva365	365 Day MA
1286	VFSUX.Adjusted_mva200	200 Day MA
1287	VFSUX.Adjusted_mva050	50 Day MA
1291	LTUIX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1292	LTUIX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1294	LTUIX.Open_Log	Log of
1295	LTUIX.Open_mva365	365 Day MA
1301	LTUIX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1302	LTUIX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1304	LTUIX.High_Log	Log of
1305	LTUIX.High_mva365	365 Day MA
1311	LTUIX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1312	LTUIX.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1314	LTUIX.Low_Log	Log of
1315	LTUIX.Low_mva365	365 Day MA
1321	LTUIX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1322	LTUIX.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1324	LTUIX.Close_Log	Log of
1325	LTUIX.Close_mva365	365 Day MA
1328	LTUIX.Volume_YoY	Year over Year
1329	LTUIX.Volume_YoY4	4 Year over 4 Year
1330	LTUIX.Volume_YoY5	5 Year over 5 Year
1331	LTUIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1332	LTUIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1333	LTUIX.Volume_SmoothDer	Derivative of Smoothed
1334	LTUIX.Volume_Log	Log of
1335	LTUIX.Volume_mva365	365 Day MA
1336	LTUIX.Volume_mva200	200 Day MA
1337	LTUIX.Volume_mva050	50 Day MA
1341	LTUIX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1342	LTUIX.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1344	LTUIX.Adjusted_Log	Log of
1345	LTUIX.Adjusted_mva365	365 Day MA
1346	LTUIX.Adjusted_mva200	200 Day MA
1347	LTUIX.Adjusted_mva050	50 Day MA
1351	PTTPX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1354	PTTPX.Open_Log	Log of
1355	PTTPX.Open_mva365	365 Day MA
1361	PTTPX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1364	PTTPX.High_Log	Log of
1365	PTTPX.High_mva365	365 Day MA
1371	PTTPX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1374	PTTPX.Low_Log	Log of
1375	PTTPX.Low_mva365	365 Day MA
1381	PTTPX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1384	PTTPX.Close_Log	Log of
1385	PTTPX.Close_mva365	365 Day MA
1388	PTTPX.Volume_YoY	Year over Year
1389	PTTPX.Volume_YoY4	4 Year over 4 Year
1390	PTTPX.Volume_YoY5	5 Year over 5 Year
1391	PTTPX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1392	PTTPX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1393	PTTPX.Volume_SmoothDer	Derivative of Smoothed
1394	PTTPX.Volume_Log	Log of
1395	PTTPX.Volume_mva365	365 Day MA
1396	PTTPX.Volume_mva200	200 Day MA
1397	PTTPX.Volume_mva050	50 Day MA
1401	PTTPX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1404	PTTPX.Adjusted_Log	Log of
1405	PTTPX.Adjusted_mva365	365 Day MA
1406	PTTPX.Adjusted_mva200	200 Day MA
1407	PTTPX.Adjusted_mva050	50 Day MA
1448	NERYX.Volume_YoY	Year over Year
1449	NERYX.Volume_YoY4	4 Year over 4 Year
1450	NERYX.Volume_YoY5	5 Year over 5 Year
1451	NERYX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1452	NERYX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1453	NERYX.Volume_SmoothDer	Derivative of Smoothed
1454	NERYX.Volume_Log	Log of
1455	NERYX.Volume_mva365	365 Day MA
1456	NERYX.Volume_mva200	200 Day MA
1457	NERYX.Volume_mva050	50 Day MA
1461	NERYX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1465	NERYX.Adjusted_mva365	365 Day MA
1508	STIGX.Volume_YoY	Year over Year
1509	STIGX.Volume_YoY4	4 Year over 4 Year
1510	STIGX.Volume_YoY5	5 Year over 5 Year
1511	STIGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1512	STIGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1513	STIGX.Volume_SmoothDer	Derivative of Smoothed
1514	STIGX.Volume_Log	Log of
1515	STIGX.Volume_mva365	365 Day MA
1516	STIGX.Volume_mva200	200 Day MA
1517	STIGX.Volume_mva050	50 Day MA
1521	STIGX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1524	STIGX.Adjusted_Log	Log of
1525	STIGX.Adjusted_mva365	365 Day MA
1531	HLGAX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1532	HLGAX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1534	HLGAX.Open_Log	Log of
1535	HLGAX.Open_mva365	365 Day MA
1541	HLGAX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1542	HLGAX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1544	HLGAX.High_Log	Log of
1545	HLGAX.High_mva365	365 Day MA
1551	HLGAX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1552	HLGAX.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1554	HLGAX.Low_Log	Log of
1555	HLGAX.Low_mva365	365 Day MA
1561	HLGAX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1562	HLGAX.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1564	HLGAX.Close_Log	Log of
1565	HLGAX.Close_mva365	365 Day MA
1568	HLGAX.Volume_YoY	Year over Year
1569	HLGAX.Volume_YoY4	4 Year over 4 Year
1570	HLGAX.Volume_YoY5	5 Year over 5 Year
1571	HLGAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1572	HLGAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1573	HLGAX.Volume_SmoothDer	Derivative of Smoothed
1574	HLGAX.Volume_Log	Log of
1575	HLGAX.Volume_mva365	365 Day MA
1576	HLGAX.Volume_mva200	200 Day MA
1577	HLGAX.Volume_mva050	50 Day MA
1581	HLGAX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1582	HLGAX.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1584	HLGAX.Adjusted_Log	Log of
1585	HLGAX.Adjusted_mva365	365 Day MA
1592	FTRGX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1594	FTRGX.Open_Log	Log of
1602	FTRGX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1604	FTRGX.High_Log	Log of
1612	FTRGX.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1614	FTRGX.Low_Log	Log of
1622	FTRGX.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1624	FTRGX.Close_Log	Log of
1628	FTRGX.Volume_YoY	Year over Year
1629	FTRGX.Volume_YoY4	4 Year over 4 Year
1630	FTRGX.Volume_YoY5	5 Year over 5 Year
1631	FTRGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1632	FTRGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1633	FTRGX.Volume_SmoothDer	Derivative of Smoothed
1634	FTRGX.Volume_Log	Log of
1635	FTRGX.Volume_mva365	365 Day MA
1636	FTRGX.Volume_mva200	200 Day MA
1637	FTRGX.Volume_mva050	50 Day MA
1641	FTRGX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1642	FTRGX.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1644	FTRGX.Adjusted_Log	Log of
1645	FTRGX.Adjusted_mva365	365 Day MA
1651	THIIX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1652	THIIX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1655	THIIX.Open_mva365	365 Day MA
1661	THIIX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1662	THIIX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1665	THIIX.High_mva365	365 Day MA
1671	THIIX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1672	THIIX.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1675	THIIX.Low_mva365	365 Day MA
1681	THIIX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1682	THIIX.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1685	THIIX.Close_mva365	365 Day MA
1688	THIIX.Volume_YoY	Year over Year
1689	THIIX.Volume_YoY4	4 Year over 4 Year
1690	THIIX.Volume_YoY5	5 Year over 5 Year
1691	THIIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1692	THIIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1693	THIIX.Volume_SmoothDer	Derivative of Smoothed
1694	THIIX.Volume_Log	Log of
1695	THIIX.Volume_mva365	365 Day MA
1696	THIIX.Volume_mva200	200 Day MA
1697	THIIX.Volume_mva050	50 Day MA
1701	THIIX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1702	THIIX.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1705	THIIX.Adjusted_mva365	365 Day MA
1706	THIIX.Adjusted_mva200	200 Day MA
1707	THIIX.Adjusted_mva050	50 Day MA
1711	PTTRX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1714	PTTRX.Open_Log	Log of
1715	PTTRX.Open_mva365	365 Day MA
1721	PTTRX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1724	PTTRX.High_Log	Log of
1725	PTTRX.High_mva365	365 Day MA
1731	PTTRX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1734	PTTRX.Low_Log	Log of
1735	PTTRX.Low_mva365	365 Day MA
1741	PTTRX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1744	PTTRX.Close_Log	Log of
1745	PTTRX.Close_mva365	365 Day MA
1748	PTTRX.Volume_YoY	Year over Year
1749	PTTRX.Volume_YoY4	4 Year over 4 Year
1750	PTTRX.Volume_YoY5	5 Year over 5 Year
1751	PTTRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1752	PTTRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1753	PTTRX.Volume_SmoothDer	Derivative of Smoothed
1754	PTTRX.Volume_Log	Log of
1755	PTTRX.Volume_mva365	365 Day MA
1756	PTTRX.Volume_mva200	200 Day MA
1757	PTTRX.Volume_mva050	50 Day MA
1761	PTTRX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1764	PTTRX.Adjusted_Log	Log of
1765	PTTRX.Adjusted_mva365	365 Day MA
1766	PTTRX.Adjusted_mva200	200 Day MA
1767	PTTRX.Adjusted_mva050	50 Day MA
1771	BFIGX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1775	BFIGX.Open_mva365	365 Day MA
1781	BFIGX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1785	BFIGX.High_mva365	365 Day MA
1791	BFIGX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1795	BFIGX.Low_mva365	365 Day MA
1801	BFIGX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1805	BFIGX.Close_mva365	365 Day MA
1808	BFIGX.Volume_YoY	Year over Year
1809	BFIGX.Volume_YoY4	4 Year over 4 Year
1810	BFIGX.Volume_YoY5	5 Year over 5 Year
1811	BFIGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1812	BFIGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1813	BFIGX.Volume_SmoothDer	Derivative of Smoothed
1814	BFIGX.Volume_Log	Log of
1815	BFIGX.Volume_mva365	365 Day MA
1816	BFIGX.Volume_mva200	200 Day MA
1817	BFIGX.Volume_mva050	50 Day MA
1821	BFIGX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1825	BFIGX.Adjusted_mva365	365 Day MA
1826	BFIGX.Adjusted_mva200	200 Day MA
1827	BFIGX.Adjusted_mva050	50 Day MA
1871	VTWO.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1872	VTWO.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1873	VTWO.Volume_SmoothDer	Derivative of Smoothed
1928	EIFAX.Volume_YoY	Year over Year
1929	EIFAX.Volume_YoY4	4 Year over 4 Year
1930	EIFAX.Volume_YoY5	5 Year over 5 Year
1931	EIFAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1932	EIFAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1933	EIFAX.Volume_SmoothDer	Derivative of Smoothed
1934	EIFAX.Volume_Log	Log of
1935	EIFAX.Volume_mva365	365 Day MA
1936	EIFAX.Volume_mva200	200 Day MA
1937	EIFAX.Volume_mva050	50 Day MA
1945	EIFAX.Adjusted_mva365	365 Day MA
1946	EIFAX.Adjusted_mva200	200 Day MA
1951	ASDAX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1952	ASDAX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1954	ASDAX.Open_Log	Log of
1955	ASDAX.Open_mva365	365 Day MA
1961	ASDAX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1962	ASDAX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1964	ASDAX.High_Log	Log of
1965	ASDAX.High_mva365	365 Day MA
1971	ASDAX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1972	ASDAX.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1974	ASDAX.Low_Log	Log of
1975	ASDAX.Low_mva365	365 Day MA
1981	ASDAX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1982	ASDAX.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1984	ASDAX.Close_Log	Log of
1985	ASDAX.Close_mva365	365 Day MA
1988	ASDAX.Volume_YoY	Year over Year
1989	ASDAX.Volume_YoY4	4 Year over 4 Year
1990	ASDAX.Volume_YoY5	5 Year over 5 Year
1991	ASDAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1992	ASDAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1993	ASDAX.Volume_SmoothDer	Derivative of Smoothed
1994	ASDAX.Volume_Log	Log of
1995	ASDAX.Volume_mva365	365 Day MA
1996	ASDAX.Volume_mva200	200 Day MA
1997	ASDAX.Volume_mva050	50 Day MA
1999	ASDAX.Adjusted_YoY4	4 Year over 4 Year
2001	ASDAX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2002	ASDAX.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2004	ASDAX.Adjusted_Log	Log of
2005	ASDAX.Adjusted_mva365	365 Day MA
2006	ASDAX.Adjusted_mva200	200 Day MA
2007	ASDAX.Adjusted_mva050	50 Day MA
2014	TRBUX.Open_Log	Log of
2015	TRBUX.Open_mva365	365 Day MA
2024	TRBUX.High_Log	Log of
2025	TRBUX.High_mva365	365 Day MA
2034	TRBUX.Low_Log	Log of
2035	TRBUX.Low_mva365	365 Day MA
2044	TRBUX.Close_Log	Log of
2045	TRBUX.Close_mva365	365 Day MA
2048	TRBUX.Volume_YoY	Year over Year
2049	TRBUX.Volume_YoY4	4 Year over 4 Year
2050	TRBUX.Volume_YoY5	5 Year over 5 Year
2051	TRBUX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2052	TRBUX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2053	TRBUX.Volume_SmoothDer	Derivative of Smoothed
2054	TRBUX.Volume_Log	Log of
2055	TRBUX.Volume_mva365	365 Day MA
2056	TRBUX.Volume_mva200	200 Day MA
2057	TRBUX.Volume_mva050	50 Day MA
2061	TRBUX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2064	TRBUX.Adjusted_Log	Log of
2065	TRBUX.Adjusted_mva365	365 Day MA
2066	TRBUX.Adjusted_mva200	200 Day MA
2067	TRBUX.Adjusted_mva050	50 Day MA
2108	PRVIX.Volume_YoY	Year over Year
2109	PRVIX.Volume_YoY4	4 Year over 4 Year
2110	PRVIX.Volume_YoY5	5 Year over 5 Year
2111	PRVIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2112	PRVIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2113	PRVIX.Volume_SmoothDer	Derivative of Smoothed
2114	PRVIX.Volume_Log	Log of
2115	PRVIX.Volume_mva365	365 Day MA
2116	PRVIX.Volume_mva200	200 Day MA
2117	PRVIX.Volume_mva050	50 Day MA
2168	PRWCX.Volume_YoY	Year over Year
2169	PRWCX.Volume_YoY4	4 Year over 4 Year
2170	PRWCX.Volume_YoY5	5 Year over 5 Year
2171	PRWCX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2172	PRWCX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2173	PRWCX.Volume_SmoothDer	Derivative of Smoothed
2174	PRWCX.Volume_Log	Log of
2175	PRWCX.Volume_mva365	365 Day MA
2176	PRWCX.Volume_mva200	200 Day MA
2177	PRWCX.Volume_mva050	50 Day MA
2185	PRWCX.Adjusted_mva365	365 Day MA
2195	ADOZX.Open_mva365	365 Day MA
2205	ADOZX.High_mva365	365 Day MA
2215	ADOZX.Low_mva365	365 Day MA
2225	ADOZX.Close_mva365	365 Day MA
2228	ADOZX.Volume_YoY	Year over Year
2229	ADOZX.Volume_YoY4	4 Year over 4 Year
2230	ADOZX.Volume_YoY5	5 Year over 5 Year
2231	ADOZX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2232	ADOZX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2233	ADOZX.Volume_SmoothDer	Derivative of Smoothed
2234	ADOZX.Volume_Log	Log of
2235	ADOZX.Volume_mva365	365 Day MA
2236	ADOZX.Volume_mva200	200 Day MA
2237	ADOZX.Volume_mva050	50 Day MA
2245	ADOZX.Adjusted_mva365	365 Day MA
2255	MERFX.Open_mva365	365 Day MA
2265	MERFX.High_mva365	365 Day MA
2275	MERFX.Low_mva365	365 Day MA
2285	MERFX.Close_mva365	365 Day MA
2288	MERFX.Volume_YoY	Year over Year
2289	MERFX.Volume_YoY4	4 Year over 4 Year
2290	MERFX.Volume_YoY5	5 Year over 5 Year
2291	MERFX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2292	MERFX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2293	MERFX.Volume_SmoothDer	Derivative of Smoothed
2294	MERFX.Volume_Log	Log of
2295	MERFX.Volume_mva365	365 Day MA
2296	MERFX.Volume_mva200	200 Day MA
2297	MERFX.Volume_mva050	50 Day MA
2301	MERFX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2303	MERFX.Adjusted_SmoothDer	Derivative of Smoothed
2305	MERFX.Adjusted_mva365	365 Day MA
2306	MERFX.Adjusted_mva200	200 Day MA
2307	MERFX.Adjusted_mva050	50 Day MA
2315	CMNIX.Open_mva365	365 Day MA
2316	CMNIX.Open_mva200	200 Day MA
2325	CMNIX.High_mva365	365 Day MA
2326	CMNIX.High_mva200	200 Day MA
2335	CMNIX.Low_mva365	365 Day MA
2336	CMNIX.Low_mva200	200 Day MA
2345	CMNIX.Close_mva365	365 Day MA
2346	CMNIX.Close_mva200	200 Day MA
2348	CMNIX.Volume_YoY	Year over Year
2349	CMNIX.Volume_YoY4	4 Year over 4 Year
2350	CMNIX.Volume_YoY5	5 Year over 5 Year
2351	CMNIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2352	CMNIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2353	CMNIX.Volume_SmoothDer	Derivative of Smoothed
2354	CMNIX.Volume_Log	Log of
2355	CMNIX.Volume_mva365	365 Day MA
2356	CMNIX.Volume_mva200	200 Day MA
2357	CMNIX.Volume_mva050	50 Day MA
2361	CMNIX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2365	CMNIX.Adjusted_mva365	365 Day MA
2366	CMNIX.Adjusted_mva200	200 Day MA
2375	CIHEX.Open_mva365	365 Day MA
2385	CIHEX.High_mva365	365 Day MA
2395	CIHEX.Low_mva365	365 Day MA
2405	CIHEX.Close_mva365	365 Day MA
2408	CIHEX.Volume_YoY	Year over Year
2409	CIHEX.Volume_YoY4	4 Year over 4 Year
2410	CIHEX.Volume_YoY5	5 Year over 5 Year
2411	CIHEX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2412	CIHEX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2413	CIHEX.Volume_SmoothDer	Derivative of Smoothed
2414	CIHEX.Volume_Log	Log of
2415	CIHEX.Volume_mva365	365 Day MA
2416	CIHEX.Volume_mva200	200 Day MA
2417	CIHEX.Volume_mva050	50 Day MA
2425	CIHEX.Adjusted_mva365	365 Day MA
2450	IMPMX_YoY5	U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 5 Year over 5 Year
2453	IMPMX_SmoothDer	Derivative of Smoothed U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA)
2460	EXPMX_YoY5	U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA) 5 Year over 5 Year
2463	EXPMX_SmoothDer	Derivative of Smoothed U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA)
2471	HSN1FNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) New One Family Houses Sold: United States (Monthly, NSA)
2473	HSN1FNSA_SmoothDer	Derivative of Smoothed New One Family Houses Sold: United States (Monthly, NSA)
2474	HSN1FNSA_Log	Log of New One Family Houses Sold: United States (Monthly, NSA)
2477	HSN1FNSA_mva050	New One Family Houses Sold: United States (Monthly, NSA) 50 Day MA
2480	HNFSUSNSA_YoY5	New One Family Houses for Sale in the United States (Monthly, NSA) 5 Year over 5 Year
2485	HNFSUSNSA_mva365	New One Family Houses for Sale in the United States (Monthly, NSA) 365 Day MA
2486	HNFSUSNSA_mva200	New One Family Houses for Sale in the United States (Monthly, NSA) 200 Day MA
2489	BUSLOANS_YoY4	Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 4 Year over 4 Year
2495	BUSLOANS_mva365	Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 365 Day MA
2505	TOTCI_mva365	Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 365 Day MA
2506	TOTCI_mva200	Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2513	BUSLOANSNSA_SmoothDer	Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2515	BUSLOANSNSA_mva365	Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 365 Day MA
2516	BUSLOANSNSA_mva200	Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2517	BUSLOANSNSA_mva050	Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2519	REALLNNSA_YoY4	Real Estate Loans, All Commercial Banks (Monthly, NSA) 4 Year over 4 Year
2525	REALLNNSA_mva365	Real Estate Loans, All Commercial Banks (Monthly, NSA) 365 Day MA
2526	REALLNNSA_mva200	Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2529	REALLN_YoY4	Real Estate Loans, All Commercial Banks (Monthly, SA) 4 Year over 4 Year
2531	REALLN_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, SA)
2533	REALLN_SmoothDer	Derivative of Smoothed Real Estate Loans, All Commercial Banks (Monthly, SA)
2534	REALLN_Log	Log of Real Estate Loans, All Commercial Banks (Monthly, SA)
2535	REALLN_mva365	Real Estate Loans, All Commercial Banks (Monthly, SA) 365 Day MA
2536	REALLN_mva200	Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2537	REALLN_mva050	Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2545	RELACBW027NBOG_mva365	Real Estate Loans, All Commercial Banks (Weekly, NSA) 365 Day MA
2546	RELACBW027NBOG_mva200	Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2551	RELACBW027SBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, SA)
2553	RELACBW027SBOG_SmoothDer	Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, SA)
2554	RELACBW027SBOG_Log	Log of Real Estate Loans, All Commercial Banks (Weekly, SA)
2555	RELACBW027SBOG_mva365	Real Estate Loans, All Commercial Banks (Weekly, SA) 365 Day MA
2556	RELACBW027SBOG_mva200	Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2557	RELACBW027SBOG_mva050	Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2559	RREACBM027NBOG_YoY4	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 4 Year over 4 Year
2565	RREACBM027NBOG_mva365	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 365 Day MA
2566	RREACBM027NBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2569	RREACBM027SBOG_YoY4	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 4 Year over 4 Year
2571	RREACBM027SBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2573	RREACBM027SBOG_SmoothDer	Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2574	RREACBM027SBOG_Log	Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2575	RREACBM027SBOG_mva365	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 365 Day MA
2576	RREACBM027SBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2577	RREACBM027SBOG_mva050	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2581	RREACBW027SBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2583	RREACBW027SBOG_SmoothDer	Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2584	RREACBW027SBOG_Log	Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2585	RREACBW027SBOG_mva365	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 365 Day MA
2586	RREACBW027SBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2587	RREACBW027SBOG_mva050	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2595	RREACBW027NBOG_mva365	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 365 Day MA
2596	RREACBW027NBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2603	MORTGAGE30US_SmoothDer	Derivative of Smoothed 30-Year Fixed Rate Mortgage Average in the United States
2610	CONSUMERNSA_YoY5	Consumer Loans, All Commercial Banks 5 Year over 5 Year
2615	CONSUMERNSA_mva365	Consumer Loans, All Commercial Banks 365 Day MA
2616	CONSUMERNSA_mva200	Consumer Loans, All Commercial Banks 200 Day MA
2619	TOTLLNSA_YoY4	Loans and Leases in Bank Credit, All Commercial Banks 4 Year over 4 Year
2621	TOTLLNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Loans and Leases in Bank Credit, All Commercial Banks
2625	TOTLLNSA_mva365	Loans and Leases in Bank Credit, All Commercial Banks 365 Day MA
2626	TOTLLNSA_mva200	Loans and Leases in Bank Credit, All Commercial Banks 200 Day MA
2627	TOTLLNSA_mva050	Loans and Leases in Bank Credit, All Commercial Banks 50 Day MA
2631	DPSACBW027SBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Deposits, All Commercial Banks
2633	DPSACBW027SBOG_SmoothDer	Derivative of Smoothed Deposits, All Commercial Banks
2634	DPSACBW027SBOG_Log	Log of Deposits, All Commercial Banks
2635	DPSACBW027SBOG_mva365	Deposits, All Commercial Banks 365 Day MA
2636	DPSACBW027SBOG_mva200	Deposits, All Commercial Banks 200 Day MA
2637	DPSACBW027SBOG_mva050	Deposits, All Commercial Banks 50 Day MA
2639	DRCLACBS_YoY4	Delinquency Rate on Consumer Loans, All Commercial Banks, SA 4 Year over 4 Year
2640	DRCLACBS_YoY5	Delinquency Rate on Consumer Loans, All Commercial Banks, SA 5 Year over 5 Year
2643	DRCLACBS_SmoothDer	Derivative of Smoothed Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2644	DRCLACBS_Log	Log of Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2645	DRCLACBS_mva365	Delinquency Rate on Consumer Loans, All Commercial Banks, SA 365 Day MA
2646	DRCLACBS_mva200	Delinquency Rate on Consumer Loans, All Commercial Banks, SA 200 Day MA
2647	DRCLACBS_mva050	Delinquency Rate on Consumer Loans, All Commercial Banks, SA 50 Day MA
2651	TOTCINSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2653	TOTCINSA_SmoothDer	Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2655	TOTCINSA_mva365	Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 365 Day MA
2656	TOTCINSA_mva200	Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2657	TOTCINSA_mva050	Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2661	SRPSABSNNCB_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2664	SRPSABSNNCB_Log	Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2665	SRPSABSNNCB_mva365	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 365 Day MA
2674	ASTLL_Log	Log of All sectors; total loans; liability, Level (NSA)
2675	ASTLL_mva365	All sectors; total loans; liability, Level (NSA) 365 Day MA
2676	ASTLL_mva200	All sectors; total loans; liability, Level (NSA) 200 Day MA
2677	ASTLL_mva050	All sectors; total loans; liability, Level (NSA) 50 Day MA
2679	FBDILNECA_YoY4	Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 4 Year over 4 Year
2684	FBDILNECA_Log	Log of Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2685	FBDILNECA_mva365	Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 365 Day MA
2686	FBDILNECA_mva200	Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 200 Day MA
2687	FBDILNECA_mva050	Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 50 Day MA
2691	ASOLAL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) All sectors; other loans and advances; liability, Level (NSA)
2694	ASOLAL_Log	Log of All sectors; other loans and advances; liability, Level (NSA)
2695	ASOLAL_mva365	All sectors; other loans and advances; liability, Level (NSA) 365 Day MA
2704	ASTMA_Log	Log of All sectors; total mortgages; asset, Level (NSA)
2705	ASTMA_mva365	All sectors; total mortgages; asset, Level (NSA) 365 Day MA
2706	ASTMA_mva200	All sectors; total mortgages; asset, Level (NSA) 200 Day MA
2707	ASTMA_mva050	All sectors; total mortgages; asset, Level (NSA) 50 Day MA
2714	ASHMA_Log	Log of All sectors; home mortgages; asset, Level (NSA)
2715	ASHMA_mva365	All sectors; home mortgages; asset, Level (NSA) 365 Day MA
2716	ASHMA_mva200	All sectors; home mortgages; asset, Level (NSA) 200 Day MA
2717	ASHMA_mva050	All sectors; home mortgages; asset, Level (NSA) 50 Day MA
2724	ASMRMA_Log	Log of All sectors; multifamily residential mortgages; asset, Level (NSA)
2725	ASMRMA_mva365	All sectors; multifamily residential mortgages; asset, Level (NSA) 365 Day MA
2726	ASMRMA_mva200	All sectors; multifamily residential mortgages; asset, Level (NSA) 200 Day MA
2727	ASMRMA_mva050	All sectors; multifamily residential mortgages; asset, Level (NSA) 50 Day MA
2734	ASCMA_Log	Log of All sectors; commercial mortgages; asset, Level (NSA)
2735	ASCMA_mva365	All sectors; commercial mortgages; asset, Level (NSA) 365 Day MA
2736	ASCMA_mva200	All sectors; commercial mortgages; asset, Level (NSA) 200 Day MA
2737	ASCMA_mva050	All sectors; commercial mortgages; asset, Level (NSA) 50 Day MA
2744	ASFMA_Log	Log of All sectors; farm mortgages; asset, Level (NSA)
2745	ASFMA_mva365	All sectors; farm mortgages; asset, Level (NSA) 365 Day MA
2746	ASFMA_mva200	All sectors; farm mortgages; asset, Level (NSA) 200 Day MA
2747	ASFMA_mva050	All sectors; farm mortgages; asset, Level (NSA) 50 Day MA
2751	CCLBSHNO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2753	CCLBSHNO_SmoothDer	Derivative of Smoothed Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2754	CCLBSHNO_Log	Log of Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2761	FBDSILQ027S_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Domestic financial sectors debt securities; liability, Level (NSA)
2764	FBDSILQ027S_Log	Log of Domestic financial sectors debt securities; liability, Level (NSA)
2765	FBDSILQ027S_mva365	Domestic financial sectors debt securities; liability, Level (NSA) 365 Day MA
2766	FBDSILQ027S_mva200	Domestic financial sectors debt securities; liability, Level (NSA) 200 Day MA
2767	FBDSILQ027S_mva050	Domestic financial sectors debt securities; liability, Level (NSA) 50 Day MA
2771	FBLL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Domestic financial sectors loans; liability, Level (NSA)
2774	FBLL_Log	Log of Domestic financial sectors loans; liability, Level (NSA)
2775	FBLL_mva365	Domestic financial sectors loans; liability, Level (NSA) 365 Day MA
2781	NCBDBIQ027S_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; debt securities; liability, Level
2784	NCBDBIQ027S_Log	Log of Nonfinancial corporate business; debt securities; liability, Level
2785	NCBDBIQ027S_mva365	Nonfinancial corporate business; debt securities; liability, Level 365 Day MA
2793	DGS10_SmoothDer	Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2796	DGS10_mva200	10-Year Treasury Constant Maturity Rate 200 Day MA
2803	TNX.Open_SmoothDer	Derivative of Smoothed
2806	TNX.Open_mva200	200 Day MA
2813	TNX.High_SmoothDer	Derivative of Smoothed
2816	TNX.High_mva200	200 Day MA
2823	TNX.Low_SmoothDer	Derivative of Smoothed
2826	TNX.Low_mva200	200 Day MA
2833	TNX.Close_SmoothDer	Derivative of Smoothed
2836	TNX.Close_mva200	200 Day MA
2838	TNX.Volume_YoY	Year over Year
2839	TNX.Volume_YoY4	4 Year over 4 Year
2840	TNX.Volume_YoY5	5 Year over 5 Year
2841	TNX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2842	TNX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2843	TNX.Volume_SmoothDer	Derivative of Smoothed
2844	TNX.Volume_Log	Log of
2845	TNX.Volume_mva365	365 Day MA
2846	TNX.Volume_mva200	200 Day MA
2847	TNX.Volume_mva050	50 Day MA
2853	TNX.Adjusted_SmoothDer	Derivative of Smoothed
2856	TNX.Adjusted_mva200	200 Day MA
2863	CLF.Open_SmoothDer	Derivative of Smoothed
2864	CLF.Open_Log	Log of
2873	CLF.High_SmoothDer	Derivative of Smoothed
2883	CLF.Low_SmoothDer	Derivative of Smoothed
2884	CLF.Low_Log	Log of
2893	CLF.Close_SmoothDer	Derivative of Smoothed
2894	CLF.Close_Log	Log of
2902	CLF.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2904	CLF.Volume_Log	Log of
2913	CLF.Adjusted_SmoothDer	Derivative of Smoothed
2914	CLF.Adjusted_Log	Log of
2923	DGS30_SmoothDer	Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2926	DGS30_mva200	10-Year Treasury Constant Maturity Rate 200 Day MA
2929	DGS1_YoY4	1-Year Treasury Constant Maturity Rate 4 Year over 4 Year
2933	DGS1_SmoothDer	Derivative of Smoothed 1-Year Treasury Constant Maturity Rate
2943	DGS2_SmoothDer	Derivative of Smoothed 2-Year Treasury Constant Maturity Rate
2949	TB3MS_YoY4	3-Month Treasury Bill: Secondary Market Rate (Monthly) 4 Year over 4 Year
2950	TB3MS_YoY5	3-Month Treasury Bill: Secondary Market Rate (Monthly) 5 Year over 5 Year
2953	TB3MS_SmoothDer	Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2963	DTB3_SmoothDer	Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Daily)
2964	DTB3_Log	Log of 3-Month Treasury Bill: Secondary Market Rate (Daily)
2973	IRX.Open_SmoothDer	Derivative of Smoothed
2974	IRX.Open_Log	Log of
2983	IRX.High_SmoothDer	Derivative of Smoothed
2984	IRX.High_Log	Log of
2993	IRX.Low_SmoothDer	Derivative of Smoothed
2994	IRX.Low_Log	Log of
3003	IRX.Close_SmoothDer	Derivative of Smoothed
3004	IRX.Close_Log	Log of
3008	IRX.Volume_YoY	Year over Year
3009	IRX.Volume_YoY4	4 Year over 4 Year
3010	IRX.Volume_YoY5	5 Year over 5 Year
3011	IRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3012	IRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3013	IRX.Volume_SmoothDer	Derivative of Smoothed
3014	IRX.Volume_Log	Log of
3015	IRX.Volume_mva365	365 Day MA
3016	IRX.Volume_mva200	200 Day MA
3017	IRX.Volume_mva050	50 Day MA
3023	IRX.Adjusted_SmoothDer	Derivative of Smoothed
3024	IRX.Adjusted_Log	Log of
3033	DCOILWTICO_SmoothDer	Derivative of Smoothed Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
3034	DCOILWTICO_Log	Log of Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
3043	DCOILBRENTEU_SmoothDer	Derivative of Smoothed Crude Oil Prices: Brent - Europe
3055	NEWORDER_mva365	Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 365 Day MA
3056	NEWORDER_mva200	Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 200 Day MA
3061	ALTSALES_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Light Weight Vehicle Sales: Autos and Light Trucks
3063	ALTSALES_SmoothDer	Derivative of Smoothed Light Weight Vehicle Sales: Autos and Light Trucks
3064	ALTSALES_Log	Log of Light Weight Vehicle Sales: Autos and Light Trucks
3065	ALTSALES_mva365	Light Weight Vehicle Sales: Autos and Light Trucks 365 Day MA
3066	ALTSALES_mva200	Light Weight Vehicle Sales: Autos and Light Trucks 200 Day MA
3067	ALTSALES_mva050	Light Weight Vehicle Sales: Autos and Light Trucks 50 Day MA
3069	ICSA_YoY4	Initial Jobless Claims 4 Year over 4 Year
3071	ICSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Initial Jobless Claims
3075	ICSA_mva365	Initial Jobless Claims 365 Day MA
3085	GSPC.Open_mva365	365 Day MA
3095	GSPC.High_mva365	365 Day MA
3119	GSPC.Volume_YoY4	4 Year over 4 Year
3121	GSPC.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3122	GSPC.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3123	GSPC.Volume_SmoothDer	Derivative of Smoothed
3125	GSPC.Volume_mva365	365 Day MA
3126	GSPC.Volume_mva200	200 Day MA
3127	GSPC.Volume_mva050	50 Day MA
3178	FXAIX.Volume_YoY	Year over Year
3179	FXAIX.Volume_YoY4	4 Year over 4 Year
3180	FXAIX.Volume_YoY5	5 Year over 5 Year
3181	FXAIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3182	FXAIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3183	FXAIX.Volume_SmoothDer	Derivative of Smoothed
3184	FXAIX.Volume_Log	Log of
3185	FXAIX.Volume_mva365	365 Day MA
3186	FXAIX.Volume_mva200	200 Day MA
3187	FXAIX.Volume_mva050	50 Day MA
3201	FTIHX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3211	FTIHX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3221	FTIHX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3231	FTIHX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3238	FTIHX.Volume_YoY	Year over Year
3239	FTIHX.Volume_YoY4	4 Year over 4 Year
3240	FTIHX.Volume_YoY5	5 Year over 5 Year
3241	FTIHX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3242	FTIHX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3243	FTIHX.Volume_SmoothDer	Derivative of Smoothed
3244	FTIHX.Volume_Log	Log of
3245	FTIHX.Volume_mva365	365 Day MA
3246	FTIHX.Volume_mva200	200 Day MA
3247	FTIHX.Volume_mva050	50 Day MA
3251	FTIHX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3253	FTIHX.Adjusted_SmoothDer	Derivative of Smoothed
3261	MDIZX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3265	MDIZX.Open_mva365	365 Day MA
3271	MDIZX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3275	MDIZX.High_mva365	365 Day MA
3281	MDIZX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3285	MDIZX.Low_mva365	365 Day MA
3291	MDIZX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3295	MDIZX.Close_mva365	365 Day MA
3298	MDIZX.Volume_YoY	Year over Year
3299	MDIZX.Volume_YoY4	4 Year over 4 Year
3300	MDIZX.Volume_YoY5	5 Year over 5 Year
3301	MDIZX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3302	MDIZX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3303	MDIZX.Volume_SmoothDer	Derivative of Smoothed
3304	MDIZX.Volume_Log	Log of
3305	MDIZX.Volume_mva365	365 Day MA
3306	MDIZX.Volume_mva200	200 Day MA
3307	MDIZX.Volume_mva050	50 Day MA
3311	MDIZX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3313	MDIZX.Adjusted_SmoothDer	Derivative of Smoothed
3315	MDIZX.Adjusted_mva365	365 Day MA
3325	DODIX.Open_mva365	365 Day MA
3335	DODIX.High_mva365	365 Day MA
3345	DODIX.Low_mva365	365 Day MA
3355	DODIX.Close_mva365	365 Day MA
3358	DODIX.Volume_YoY	Year over Year
3359	DODIX.Volume_YoY4	4 Year over 4 Year
3360	DODIX.Volume_YoY5	5 Year over 5 Year
3361	DODIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3362	DODIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3363	DODIX.Volume_SmoothDer	Derivative of Smoothed
3364	DODIX.Volume_Log	Log of
3365	DODIX.Volume_mva365	365 Day MA
3366	DODIX.Volume_mva200	200 Day MA
3367	DODIX.Volume_mva050	50 Day MA
3371	DODIX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3374	DODIX.Adjusted_Log	Log of
3375	DODIX.Adjusted_mva365	365 Day MA
3385	RLG.Open_mva365	365 Day MA
3395	RLG.High_mva365	365 Day MA
3418	RLG.Volume_YoY	Year over Year
3419	RLG.Volume_YoY4	4 Year over 4 Year
3420	RLG.Volume_YoY5	5 Year over 5 Year
3421	RLG.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3422	RLG.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3423	RLG.Volume_SmoothDer	Derivative of Smoothed
3424	RLG.Volume_Log	Log of
3425	RLG.Volume_mva365	365 Day MA
3426	RLG.Volume_mva200	200 Day MA
3427	RLG.Volume_mva050	50 Day MA
3445	DJI.Open_mva365	365 Day MA
3455	DJI.High_mva365	365 Day MA
3481	DJI.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3482	DJI.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3483	DJI.Volume_SmoothDer	Derivative of Smoothed
3484	DJI.Volume_Log	Log of
3485	DJI.Volume_mva365	365 Day MA
3486	DJI.Volume_mva200	200 Day MA
3487	DJI.Volume_mva050	50 Day MA
3501	STOXX50E.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3503	STOXX50E.Open_SmoothDer	Derivative of Smoothed
3505	STOXX50E.Open_mva365	365 Day MA
3506	STOXX50E.Open_mva200	200 Day MA
3511	STOXX50E.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3513	STOXX50E.High_SmoothDer	Derivative of Smoothed
3515	STOXX50E.High_mva365	365 Day MA
3516	STOXX50E.High_mva200	200 Day MA
3521	STOXX50E.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3523	STOXX50E.Low_SmoothDer	Derivative of Smoothed
3531	STOXX50E.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3533	STOXX50E.Close_SmoothDer	Derivative of Smoothed
3541	STOXX50E.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3542	STOXX50E.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3543	STOXX50E.Volume_SmoothDer	Derivative of Smoothed
3544	STOXX50E.Volume_Log	Log of
3546	STOXX50E.Volume_mva200	200 Day MA
3547	STOXX50E.Volume_mva050	50 Day MA
3551	STOXX50E.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3553	STOXX50E.Adjusted_SmoothDer	Derivative of Smoothed
3561	EFA.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3563	EFA.Open_SmoothDer	Derivative of Smoothed
3571	EFA.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3573	EFA.High_SmoothDer	Derivative of Smoothed
3581	EFA.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3583	EFA.Low_SmoothDer	Derivative of Smoothed
3591	EFA.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3593	EFA.Close_SmoothDer	Derivative of Smoothed
3598	EFA.Volume_YoY	Year over Year
3601	EFA.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3602	EFA.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3603	EFA.Volume_SmoothDer	Derivative of Smoothed
3604	EFA.Volume_Log	Log of
3606	EFA.Volume_mva200	200 Day MA
3607	EFA.Volume_mva050	50 Day MA
3611	EFA.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3613	EFA.Adjusted_SmoothDer	Derivative of Smoothed
3624	GDP_Log	Log of Gross Domestic Product
3625	GDP_mva365	Gross Domestic Product 365 Day MA
3626	GDP_mva200	Gross Domestic Product 200 Day MA
3627	GDP_mva050	Gross Domestic Product 50 Day MA
3634	FNDEFX_Log	Log of Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3635	FNDEFX_mva365	Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 365 Day MA
3636	FNDEFX_mva200	Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3637	FNDEFX_mva050	Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3644	FDEFX_Log	Log of Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3645	FDEFX_mva365	Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 365 Day MA
3646	FDEFX_mva200	Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3647	FDEFX_mva050	Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3654	GDPNOW_Log	Log of Fed Atlanta GDPNow
3664	GDPC1_Log	Log of Real Gross Domestic Product
3665	GDPC1_mva365	Real Gross Domestic Product 365 Day MA
3666	GDPC1_mva200	Real Gross Domestic Product 200 Day MA
3667	GDPC1_mva050	Real Gross Domestic Product 50 Day MA
3674	GDPDEF_Log	Log of Gross Domestic Product: Implicit Price Deflator
3675	GDPDEF_mva365	Gross Domestic Product: Implicit Price Deflator 365 Day MA
3676	GDPDEF_mva200	Gross Domestic Product: Implicit Price Deflator 200 Day MA
3677	GDPDEF_mva050	Gross Domestic Product: Implicit Price Deflator 50 Day MA
3685	VIG.Open_mva365	365 Day MA
3695	VIG.High_mva365	365 Day MA
3719	VIG.Volume_YoY4	4 Year over 4 Year
3721	VIG.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3722	VIG.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3723	VIG.Volume_SmoothDer	Derivative of Smoothed
3724	VIG.Volume_Log	Log of
3726	VIG.Volume_mva200	200 Day MA
3727	VIG.Volume_mva050	50 Day MA
3735	VIG.Adjusted_mva365	365 Day MA
3749	FEDFUNDS_YoY4	Effective Federal Funds Rate 4 Year over 4 Year
3750	FEDFUNDS_YoY5	Effective Federal Funds Rate 5 Year over 5 Year
3753	FEDFUNDS_SmoothDer	Derivative of Smoothed Effective Federal Funds Rate
3761	GPDI_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Gross Private Domestic Investment
3763	GPDI_SmoothDer	Derivative of Smoothed Gross Private Domestic Investment
3764	GPDI_Log	Log of Gross Private Domestic Investment
3771	W790RC1Q027SBEA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Net domestic investment: Private: Domestic busines
3773	W790RC1Q027SBEA_SmoothDer	Derivative of Smoothed Net domestic investment: Private: Domestic busines
3774	W790RC1Q027SBEA_Log	Log of Net domestic investment: Private: Domestic busines
3778	MZMV_YoY	Velocity of MZM Money Stock Year over Year
3779	MZMV_YoY4	Velocity of MZM Money Stock 4 Year over 4 Year
3784	MZMV_Log	Log of Velocity of MZM Money Stock
3785	MZMV_mva365	Velocity of MZM Money Stock 365 Day MA
3786	MZMV_mva200	Velocity of MZM Money Stock 200 Day MA
3787	MZMV_mva050	Velocity of MZM Money Stock 50 Day MA
3788	M1_YoY	M1 Money Stock Year over Year
3794	M1_Log	Log of M1 Money Stock
3795	M1_mva365	M1 Money Stock 365 Day MA
3796	M1_mva200	M1 Money Stock 200 Day MA
3797	M1_mva050	M1 Money Stock 50 Day MA
3798	M2_YoY	M2 Money Stock Year over Year
3804	M2_Log	Log of M2 Money Stock
3805	M2_mva365	M2 Money Stock 365 Day MA
3806	M2_mva200	M2 Money Stock 200 Day MA
3807	M2_mva050	M2 Money Stock 50 Day MA
3814	OPHNFB_Log	Log of Nonfarm Business Sector: Real Output Per Hour of All Persons, SA
3815	OPHNFB_mva365	Nonfarm Business Sector: Real Output Per Hour of All Persons, SA 365 Day MA
3816	OPHNFB_mva200	Nonfarm Business Sector: Real Output Per Hour of All Persons, SA 200 Day MA
3817	OPHNFB_mva050	Nonfarm Business Sector: Real Output Per Hour of All Persons, SA 50 Day MA
3821	IPMAN_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Industrial Production: Manufacturing (NAICS)
3823	IPMAN_SmoothDer	Derivative of Smoothed Industrial Production: Manufacturing (NAICS)
3824	IPMAN_Log	Log of Industrial Production: Manufacturing (NAICS)
3825	IPMAN_mva365	Industrial Production: Manufacturing (NAICS) 365 Day MA
3826	IPMAN_mva200	Industrial Production: Manufacturing (NAICS) 200 Day MA
3827	IPMAN_mva050	Industrial Production: Manufacturing (NAICS) 50 Day MA
3835	IWD.Open_mva365	365 Day MA
3872	IWD.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3876	IWD.Volume_mva200	200 Day MA
3890	GS5_YoY5	5-Year Treasury Constant Maturity Rate 5 Year over 5 Year
3893	GS5_SmoothDer	Derivative of Smoothed 5-Year Treasury Constant Maturity Rate
3896	GS5_mva200	5-Year Treasury Constant Maturity Rate 200 Day MA
3898	PSAVERT_YoY	Personal Saving Rate Year over Year
3899	PSAVERT_YoY4	Personal Saving Rate 4 Year over 4 Year
3901	PSAVERT_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Personal Saving Rate
3903	PSAVERT_SmoothDer	Derivative of Smoothed Personal Saving Rate
3904	PSAVERT_Log	Log of Personal Saving Rate
3907	PSAVERT_mva050	Personal Saving Rate 50 Day MA
3908	VIXCLS_YoY	CBOE Volatility Index Year over Year
3909	VIXCLS_YoY4	CBOE Volatility Index 4 Year over 4 Year
3911	VIXCLS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) CBOE Volatility Index
3912	VIXCLS_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) CBOE Volatility Index
3913	VIXCLS_SmoothDer	Derivative of Smoothed CBOE Volatility Index
3914	VIXCLS_Log	Log of CBOE Volatility Index
3915	VIXCLS_mva365	CBOE Volatility Index 365 Day MA
3916	VIXCLS_mva200	CBOE Volatility Index 200 Day MA
3917	VIXCLS_mva050	CBOE Volatility Index 50 Day MA
3919	VXX.Open_YoY4	4 Year over 4 Year
3921	VXX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3922	VXX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3924	VXX.Open_Log	Log of
3928	VXX.High_YoY	Year over Year
3929	VXX.High_YoY4	4 Year over 4 Year
3931	VXX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3932	VXX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3933	VXX.High_SmoothDer	Derivative of Smoothed
3934	VXX.High_Log	Log of
3939	VXX.Low_YoY4	4 Year over 4 Year
3941	VXX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3942	VXX.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3944	VXX.Low_Log	Log of
3948	VXX.Close_YoY	Year over Year
3949	VXX.Close_YoY4	4 Year over 4 Year
3951	VXX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3952	VXX.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3953	VXX.Close_SmoothDer	Derivative of Smoothed
3954	VXX.Close_Log	Log of
3961	VXX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3962	VXX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3963	VXX.Volume_SmoothDer	Derivative of Smoothed
3964	VXX.Volume_Log	Log of
3965	VXX.Volume_mva365	365 Day MA
3966	VXX.Volume_mva200	200 Day MA
3967	VXX.Volume_mva050	50 Day MA
3968	VXX.Adjusted_YoY	Year over Year
3969	VXX.Adjusted_YoY4	4 Year over 4 Year
3971	VXX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3972	VXX.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3973	VXX.Adjusted_SmoothDer	Derivative of Smoothed
3974	VXX.Adjusted_Log	Log of
3978	HOUST1F_YoY	Privately Owned Housing Starts: 1-Unit Structures Year over Year
3981	HOUST1F_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Privately Owned Housing Starts: 1-Unit Structures
3983	HOUST1F_SmoothDer	Derivative of Smoothed Privately Owned Housing Starts: 1-Unit Structures
3984	HOUST1F_Log	Log of Privately Owned Housing Starts: 1-Unit Structures
3986	HOUST1F_mva200	Privately Owned Housing Starts: 1-Unit Structures 200 Day MA
3987	HOUST1F_mva050	Privately Owned Housing Starts: 1-Unit Structures 50 Day MA
3994	GFDEBTN_Log	Log of Federal Debt: Total Public Debt
3995	GFDEBTN_mva365	Federal Debt: Total Public Debt 365 Day MA
3996	GFDEBTN_mva200	Federal Debt: Total Public Debt 200 Day MA
3997	GFDEBTN_mva050	Federal Debt: Total Public Debt 50 Day MA
4001	HOUST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Housing Starts: Total: New Privately Owned Housing Units Started, SA
4006	HOUST_mva200	Housing Starts: Total: New Privately Owned Housing Units Started, SA 200 Day MA
4007	HOUST_mva050	Housing Starts: Total: New Privately Owned Housing Units Started, SA 50 Day MA
4011	HOUSTNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Housing Starts: Total: New Privately Owned Housing Units Started, NSA
4013	HOUSTNSA_SmoothDer	Derivative of Smoothed Housing Starts: Total: New Privately Owned Housing Units Started, NSA
4014	HOUSTNSA_Log	Log of Housing Starts: Total: New Privately Owned Housing Units Started, NSA
4018	EXHOSLUSM495S_YoY	Existing Home Sales Year over Year
4026	EXHOSLUSM495S_mva200	Existing Home Sales 200 Day MA
4027	EXHOSLUSM495S_mva050	Existing Home Sales 50 Day MA
4034	MSPUS_Log	Log of Median Sales Price of Houses Sold for the United States (NSA)
4036	MSPUS_mva200	Median Sales Price of Houses Sold for the United States (NSA) 200 Day MA
4037	MSPUS_mva050	Median Sales Price of Houses Sold for the United States (NSA) 50 Day MA
4051	DGORDER_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Manufacturers’ New Orders: Durable Goods (SA)
4054	DGORDER_Log	Log of Manufacturers’ New Orders: Durable Goods (SA)
4055	DGORDER_mva365	Manufacturers’ New Orders: Durable Goods (SA) 365 Day MA
4056	DGORDER_mva200	Manufacturers’ New Orders: Durable Goods (SA) 200 Day MA
4057	DGORDER_mva050	Manufacturers’ New Orders: Durable Goods (SA) 50 Day MA
4063	CSUSHPINSA_SmoothDer	Derivative of Smoothed S&P/Case-Shiller U.S. National Home Price Index (NSA)
4065	CSUSHPINSA_mva365	S&P/Case-Shiller U.S. National Home Price Index (NSA) 365 Day MA
4069	GFDEGDQ188S_YoY4	Federal Debt: Total Public Debt as Percent of Gross Domestic Product 4 Year over 4 Year
4074	GFDEGDQ188S_Log	Log of Federal Debt: Total Public Debt as Percent of Gross Domestic Product
4075	GFDEGDQ188S_mva365	Federal Debt: Total Public Debt as Percent of Gross Domestic Product 365 Day MA
4076	GFDEGDQ188S_mva200	Federal Debt: Total Public Debt as Percent of Gross Domestic Product 200 Day MA
4077	GFDEGDQ188S_mva050	Federal Debt: Total Public Debt as Percent of Gross Domestic Product 50 Day MA
4079	FYFSD_YoY4	Federal Surplus or Deficit 4 Year over 4 Year
4083	FYFSD_SmoothDer	Derivative of Smoothed Federal Surplus or Deficit
4084	FYFSD_Log	Log of Federal Surplus or Deficit
4089	FYFSGDA188S_YoY4	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 4 Year over 4 Year
4092	FYFSGDA188S_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
4094	FYFSGDA188S_Log	Log of Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
4096	FYFSGDA188S_mva200	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 200 Day MA
4097	FYFSGDA188S_mva050	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 50 Day MA
4101	GDX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4105	GDX.Open_mva365	365 Day MA
4106	GDX.Open_mva200	200 Day MA
4107	GDX.Open_mva050	50 Day MA
4111	GDX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4115	GDX.High_mva365	365 Day MA
4116	GDX.High_mva200	200 Day MA
4117	GDX.High_mva050	50 Day MA
4121	GDX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4125	GDX.Low_mva365	365 Day MA
4126	GDX.Low_mva200	200 Day MA
4127	GDX.Low_mva050	50 Day MA
4131	GDX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4135	GDX.Close_mva365	365 Day MA
4136	GDX.Close_mva200	200 Day MA
4137	GDX.Close_mva050	50 Day MA
4140	GDX.Volume_YoY5	5 Year over 5 Year
4141	GDX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4142	GDX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4143	GDX.Volume_SmoothDer	Derivative of Smoothed
4144	GDX.Volume_Log	Log of
4151	GDX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4155	GDX.Adjusted_mva365	365 Day MA
4156	GDX.Adjusted_mva200	200 Day MA
4157	GDX.Adjusted_mva050	50 Day MA
4163	XLE.Open_SmoothDer	Derivative of Smoothed
4173	XLE.High_SmoothDer	Derivative of Smoothed
4183	XLE.Low_SmoothDer	Derivative of Smoothed
4193	XLE.Close_SmoothDer	Derivative of Smoothed
4201	XLE.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4202	XLE.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4203	XLE.Volume_SmoothDer	Derivative of Smoothed
4204	XLE.Volume_Log	Log of
4206	XLE.Volume_mva200	200 Day MA
4207	XLE.Volume_mva050	50 Day MA
4213	XLE.Adjusted_SmoothDer	Derivative of Smoothed
4221	GSG.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4223	GSG.Open_SmoothDer	Derivative of Smoothed
4226	GSG.Open_mva200	200 Day MA
4231	GSG.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4233	GSG.High_SmoothDer	Derivative of Smoothed
4236	GSG.High_mva200	200 Day MA
4241	GSG.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4243	GSG.Low_SmoothDer	Derivative of Smoothed
4251	GSG.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4253	GSG.Close_SmoothDer	Derivative of Smoothed
4256	GSG.Close_mva200	200 Day MA
4261	GSG.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4263	GSG.Volume_SmoothDer	Derivative of Smoothed
4267	GSG.Volume_mva050	50 Day MA
4271	GSG.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4273	GSG.Adjusted_SmoothDer	Derivative of Smoothed
4276	GSG.Adjusted_mva200	200 Day MA
4278	WALCL_YoY	All Federal Reserve Banks: Total Assets Year over Year
4283	WALCL_SmoothDer	Derivative of Smoothed All Federal Reserve Banks: Total Assets
4293	OUTMS_SmoothDer	Derivative of Smoothed Manufacturing Sector: Real Output
4294	OUTMS_Log	Log of Manufacturing Sector: Real Output
4301	MANEMP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) All Employees: Manufacturing
4303	MANEMP_SmoothDer	Derivative of Smoothed All Employees: Manufacturing
4313	PRS30006163_SmoothDer	Derivative of Smoothed Manufacturing Sector: Real Output Per Person
4314	PRS30006163_Log	Log of Manufacturing Sector: Real Output Per Person
4317	PRS30006163_mva050	Manufacturing Sector: Real Output Per Person 50 Day MA
4318	BAMLC0A3CA_YoY	ICE BofAML US Corporate A Option-Adjusted Spread Year over Year
4319	BAMLC0A3CA_YoY4	ICE BofAML US Corporate A Option-Adjusted Spread 4 Year over 4 Year
4321	BAMLC0A3CA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) ICE BofAML US Corporate A Option-Adjusted Spread
4322	BAMLC0A3CA_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) ICE BofAML US Corporate A Option-Adjusted Spread
4323	BAMLC0A3CA_SmoothDer	Derivative of Smoothed ICE BofAML US Corporate A Option-Adjusted Spread
4324	BAMLC0A3CA_Log	Log of ICE BofAML US Corporate A Option-Adjusted Spread
4333	AAA_SmoothDer	Derivative of Smoothed Moody’s Seasoned Aaa Corporate Bond Yield
4335	AAA_mva365	Moody’s Seasoned Aaa Corporate Bond Yield 365 Day MA
4336	AAA_mva200	Moody’s Seasoned Aaa Corporate Bond Yield 200 Day MA
4343	SOFR_SmoothDer	Derivative of Smoothed Secured Overnight Financing Rate
4351	SOFRVOL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Volume
4355	SOFRVOL_mva365	Secured Overnight Financing Volume 365 Day MA
4356	SOFRVOL_mva200	Secured Overnight Financing Volume 200 Day MA
4357	SOFRVOL_mva050	Secured Overnight Financing Volume 50 Day MA
4373	SOFR75_SmoothDer	Derivative of Smoothed Secured Overnight Financing Rate: 75th Percentile
4383	SOFR25_SmoothDer	Derivative of Smoothed Secured Overnight Financing Rate: 25th Percentile
4384	SOFR25_Log	Log of Secured Overnight Financing Rate: 25th Percentile
4393	SOFR1_SmoothDer	Derivative of Smoothed Secured Overnight Financing Rate: 1st Percentile
4394	SOFR1_Log	Log of Secured Overnight Financing Rate: 1st Percentile
4400	OBFR_YoY5	Overnight Bank Funding Rate 5 Year over 5 Year
4403	OBFR_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate
4410	OBFR99_YoY5	Overnight Bank Funding Rate: 99th Percentile 5 Year over 5 Year
4413	OBFR99_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate: 99th Percentile
4420	OBFR75_YoY5	Overnight Bank Funding Rate: 75th Percentile 5 Year over 5 Year
4423	OBFR75_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate: 75th Percentile
4433	OBFR25_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate: 25th Percentile
4443	OBFR1_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate: 1st Percentile
4454	RPONTSYD_Log	Log of Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4458	IOER_YoY	Interest Rate on Excess Reserves Year over Year
4459	IOER_YoY4	Interest Rate on Excess Reserves 4 Year over 4 Year
4460	IOER_YoY5	Interest Rate on Excess Reserves 5 Year over 5 Year
4464	IOER_Log	Log of Interest Rate on Excess Reserves
4465	IOER_mva365	Interest Rate on Excess Reserves 365 Day MA
4466	IOER_mva200	Interest Rate on Excess Reserves 200 Day MA
4467	IOER_mva050	Interest Rate on Excess Reserves 50 Day MA
4471	WRESBAL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Reserve Balances with Federal Reserve Banks
4473	WRESBAL_SmoothDer	Derivative of Smoothed Reserve Balances with Federal Reserve Banks
4477	WRESBAL_mva050	Reserve Balances with Federal Reserve Banks 50 Day MA
4478	EXCSRESNW_YoY	Excess Reserves of Depository Institutions Year over Year
4479	EXCSRESNW_YoY4	Excess Reserves of Depository Institutions 4 Year over 4 Year
4484	EXCSRESNW_Log	Log of Excess Reserves of Depository Institutions
4485	EXCSRESNW_mva365	Excess Reserves of Depository Institutions 365 Day MA
4486	EXCSRESNW_mva200	Excess Reserves of Depository Institutions 200 Day MA
4487	EXCSRESNW_mva050	Excess Reserves of Depository Institutions 50 Day MA
4488	ECBASSETS_YoY	Central Bank Assets for Euro Area (11-19 Countries) Year over Year
4489	ECBASSETS_YoY4	Central Bank Assets for Euro Area (11-19 Countries) 4 Year over 4 Year
4490	ECBASSETS_YoY5	Central Bank Assets for Euro Area (11-19 Countries) 5 Year over 5 Year
4494	ECBASSETS_Log	Log of Central Bank Assets for Euro Area (11-19 Countries)
4495	ECBASSETS_mva365	Central Bank Assets for Euro Area (11-19 Countries) 365 Day MA
4496	ECBASSETS_mva200	Central Bank Assets for Euro Area (11-19 Countries) 200 Day MA
4497	ECBASSETS_mva050	Central Bank Assets for Euro Area (11-19 Countries) 50 Day MA
4504	EUNNGDP_Log	Log of Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
4505	EUNNGDP_mva365	Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 365 Day MA
4506	EUNNGDP_mva200	Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 200 Day MA
4507	EUNNGDP_mva050	Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 50 Day MA
4511	CEU0600000007_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4515	CEU0600000007_mva365	Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing 365 Day MA
4518	CURRENCY_YoY	Currency Component of M1 (Seasonally Adjusted) Year over Year
4524	CURRENCY_Log	Log of Currency Component of M1 (Seasonally Adjusted)
4525	CURRENCY_mva365	Currency Component of M1 (Seasonally Adjusted) 365 Day MA
4526	CURRENCY_mva200	Currency Component of M1 (Seasonally Adjusted) 200 Day MA
4527	CURRENCY_mva050	Currency Component of M1 (Seasonally Adjusted) 50 Day MA
4535	WCURRNS_mva365	Currency Component of M1 365 Day MA
4536	WCURRNS_mva200	Currency Component of M1 200 Day MA
4541	BOGMBASE_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Monetary Base; Total
4543	BOGMBASE_SmoothDer	Derivative of Smoothed Monetary Base; Total
4551	PRS88003193_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial Corporations Sector: Unit Profits
4554	PRS88003193_Log	Log of Nonfinancial Corporations Sector: Unit Profits
4555	PRS88003193_mva365	Nonfinancial Corporations Sector: Unit Profits 365 Day MA
4556	PRS88003193_mva200	Nonfinancial Corporations Sector: Unit Profits 200 Day MA
4557	PRS88003193_mva050	Nonfinancial Corporations Sector: Unit Profits 50 Day MA
4561	PPIACO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index for All Commodities
4563	PPIACO_SmoothDer	Derivative of Smoothed Producer Price Index for All Commodities
4564	PPIACO_Log	Log of Producer Price Index for All Commodities
4565	PPIACO_mva365	Producer Price Index for All Commodities 365 Day MA
4566	PPIACO_mva200	Producer Price Index for All Commodities 200 Day MA
4567	PPIACO_mva050	Producer Price Index for All Commodities 50 Day MA
4571	PCUOMFGOMFG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index by Industry: Total Manufacturing Industries
4573	PCUOMFGOMFG_SmoothDer	Derivative of Smoothed Producer Price Index by Industry: Total Manufacturing Industries
4574	PCUOMFGOMFG_Log	Log of Producer Price Index by Industry: Total Manufacturing Industries
4577	PCUOMFGOMFG_mva050	Producer Price Index by Industry: Total Manufacturing Industries 50 Day MA
4584	POPTHM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Population (U.S.)
4585	POPTHM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Population (U.S.)
4590	POPTHM_Log	Log of Population (U.S.)
4591	POPTHM_Log	Log of Population (U.S.)
4592	POPTHM_mva365	Population (U.S.) 365 Day MA
4593	POPTHM_mva365	Population (U.S.) 365 Day MA
4594	POPTHM_mva200	Population (U.S.) 200 Day MA
4595	POPTHM_mva200	Population (U.S.) 200 Day MA
4596	POPTHM_mva050	Population (U.S.) 50 Day MA
4597	POPTHM_mva050	Population (U.S.) 50 Day MA
4604	POPTHM.1_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4605	POPTHM.1_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4610	POPTHM.1_Log	Log of
4611	POPTHM.1_Log	Log of
4612	POPTHM.1_mva365	365 Day MA
4613	POPTHM.1_mva365	365 Day MA
4614	POPTHM.1_mva200	200 Day MA
4615	POPTHM.1_mva200	200 Day MA
4616	POPTHM.1_mva050	50 Day MA
4617	POPTHM.1_mva050	50 Day MA
4621	CLF16OV_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Civilian Labor Force Level, SA
4623	CLF16OV_SmoothDer	Derivative of Smoothed Civilian Labor Force Level, SA
4625	CLF16OV_mva365	Civilian Labor Force Level, SA 365 Day MA
4626	CLF16OV_mva200	Civilian Labor Force Level, SA 200 Day MA
4627	CLF16OV_mva050	Civilian Labor Force Level, SA 50 Day MA
4631	LNU01000000_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Civilian Labor Force Level, NSA
4633	LNU01000000_SmoothDer	Derivative of Smoothed Civilian Labor Force Level, NSA
4634	LNU01000000_Log	Log of Civilian Labor Force Level, NSA
4635	LNU01000000_mva365	Civilian Labor Force Level, NSA 365 Day MA
4636	LNU01000000_mva200	Civilian Labor Force Level, NSA 200 Day MA
4637	LNU01000000_mva050	Civilian Labor Force Level, NSA 50 Day MA
4639	LNU03000000_YoY4	Unemployment Level (NSA) 4 Year over 4 Year
4641	LNU03000000_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Unemployment Level (NSA)
4643	LNU03000000_SmoothDer	Derivative of Smoothed Unemployment Level (NSA)
4645	LNU03000000_mva365	Unemployment Level (NSA) 365 Day MA
4646	LNU03000000_mva200	Unemployment Level (NSA) 200 Day MA
4649	UNEMPLOY_YoY4	Unemployment Level, seasonally adjusted 4 Year over 4 Year
4651	UNEMPLOY_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Unemployment Level, seasonally adjusted
4655	UNEMPLOY_mva365	Unemployment Level, seasonally adjusted 365 Day MA
4656	UNEMPLOY_mva200	Unemployment Level, seasonally adjusted 200 Day MA
4657	UNEMPLOY_mva050	Unemployment Level, seasonally adjusted 50 Day MA
4665	RSAFS_mva365	Advance Retail Sales: Retail and Food Services 365 Day MA
4666	RSAFS_mva200	Advance Retail Sales: Retail and Food Services 200 Day MA
4671	FRGSHPUSM649NCIS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Cass Freight Index: Shipments
4673	FRGSHPUSM649NCIS_SmoothDer	Derivative of Smoothed Cass Freight Index: Shipments
4684	BOPGTB_Log	Log of Trade Balance: Goods, Balance of Payments Basis (SA)
4690	TERMCBPER24NS_YoY5	Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 5 Year over 5 Year
4703	A065RC1A027NBEA_SmoothDer	Derivative of Smoothed Personal income (NSA)
4704	A065RC1A027NBEA_Log	Log of Personal income (NSA)
4705	A065RC1A027NBEA_mva365	Personal income (NSA) 365 Day MA
4706	A065RC1A027NBEA_mva200	Personal income (NSA) 200 Day MA
4707	A065RC1A027NBEA_mva050	Personal income (NSA) 50 Day MA
4711	PI_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Personal income (SA)
4713	PI_SmoothDer	Derivative of Smoothed Personal income (SA)
4714	PI_Log	Log of Personal income (SA)
4715	PI_mva365	Personal income (SA) 365 Day MA
4716	PI_mva200	Personal income (SA) 200 Day MA
4717	PI_mva050	Personal income (SA) 50 Day MA
4724	PCE_Log	Log of Personal Consumption Expenditures (SA)
4725	PCE_mva365	Personal Consumption Expenditures (SA) 365 Day MA
4726	PCE_mva200	Personal Consumption Expenditures (SA) 200 Day MA
4727	PCE_mva050	Personal Consumption Expenditures (SA) 50 Day MA
4734	A053RC1Q027SBEA_Log	Log of National income: Corporate profits before tax (without IVA and CCAdj)
4735	A053RC1Q027SBEA_mva365	National income: Corporate profits before tax (without IVA and CCAdj) 365 Day MA
4736	A053RC1Q027SBEA_mva200	National income: Corporate profits before tax (without IVA and CCAdj) 200 Day MA
4737	A053RC1Q027SBEA_mva050	National income: Corporate profits before tax (without IVA and CCAdj) 50 Day MA
4744	CPROFIT_Log	Log of Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4745	CPROFIT_mva365	Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 365 Day MA
4746	CPROFIT_mva200	Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 200 Day MA
4747	CPROFIT_mva050	Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 50 Day MA
4755	SPY.Open_mva365	365 Day MA
4765	SPY.High_mva365	365 Day MA
4788	SPY.Volume_YoY	Year over Year
4791	SPY.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4792	SPY.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4793	SPY.Volume_SmoothDer	Derivative of Smoothed
4794	SPY.Volume_Log	Log of
4797	SPY.Volume_mva050	50 Day MA
4848	MDY.Volume_YoY	Year over Year
4849	MDY.Volume_YoY4	4 Year over 4 Year
4851	MDY.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4852	MDY.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4853	MDY.Volume_SmoothDer	Derivative of Smoothed
4854	MDY.Volume_Log	Log of
4855	MDY.Volume_mva365	365 Day MA
4856	MDY.Volume_mva200	200 Day MA
4857	MDY.Volume_mva050	50 Day MA
4911	EES.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4913	EES.Volume_SmoothDer	Derivative of Smoothed
4914	EES.Volume_Log	Log of
4916	EES.Volume_mva200	200 Day MA
4968	IJR.Volume_YoY	Year over Year
4971	IJR.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4972	IJR.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4973	IJR.Volume_SmoothDer	Derivative of Smoothed
4974	IJR.Volume_Log	Log of
4976	IJR.Volume_mva200	200 Day MA
4977	IJR.Volume_mva050	50 Day MA
5028	VGSTX.Volume_YoY	Year over Year
5029	VGSTX.Volume_YoY4	4 Year over 4 Year
5030	VGSTX.Volume_YoY5	5 Year over 5 Year
5031	VGSTX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5032	VGSTX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5033	VGSTX.Volume_SmoothDer	Derivative of Smoothed
5034	VGSTX.Volume_Log	Log of
5035	VGSTX.Volume_mva365	365 Day MA
5036	VGSTX.Volume_mva200	200 Day MA
5037	VGSTX.Volume_mva050	50 Day MA
5088	VFINX.Volume_YoY	Year over Year
5089	VFINX.Volume_YoY4	4 Year over 4 Year
5090	VFINX.Volume_YoY5	5 Year over 5 Year
5091	VFINX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5092	VFINX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5093	VFINX.Volume_SmoothDer	Derivative of Smoothed
5094	VFINX.Volume_Log	Log of
5095	VFINX.Volume_mva365	365 Day MA
5096	VFINX.Volume_mva200	200 Day MA
5097	VFINX.Volume_mva050	50 Day MA
5151	VOE.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5152	VOE.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5153	VOE.Volume_SmoothDer	Derivative of Smoothed
5154	VOE.Volume_Log	Log of
5156	VOE.Volume_mva200	200 Day MA
5157	VOE.Volume_mva050	50 Day MA
5211	VOT.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5212	VOT.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5213	VOT.Volume_SmoothDer	Derivative of Smoothed
5215	VOT.Volume_mva365	365 Day MA
5216	VOT.Volume_mva200	200 Day MA
5217	VOT.Volume_mva050	50 Day MA
5228	TMFGX.Open_YoY	Year over Year
5234	TMFGX.Open_Log	Log of
5235	TMFGX.Open_mva365	365 Day MA
5236	TMFGX.Open_mva200	200 Day MA
5237	TMFGX.Open_mva050	50 Day MA
5238	TMFGX.High_YoY	Year over Year
5244	TMFGX.High_Log	Log of
5245	TMFGX.High_mva365	365 Day MA
5246	TMFGX.High_mva200	200 Day MA
5247	TMFGX.High_mva050	50 Day MA
5248	TMFGX.Low_YoY	Year over Year
5254	TMFGX.Low_Log	Log of
5255	TMFGX.Low_mva365	365 Day MA
5256	TMFGX.Low_mva200	200 Day MA
5257	TMFGX.Low_mva050	50 Day MA
5258	TMFGX.Close_YoY	Year over Year
5264	TMFGX.Close_Log	Log of
5265	TMFGX.Close_mva365	365 Day MA
5266	TMFGX.Close_mva200	200 Day MA
5267	TMFGX.Close_mva050	50 Day MA
5268	TMFGX.Volume_YoY	Year over Year
5269	TMFGX.Volume_YoY4	4 Year over 4 Year
5270	TMFGX.Volume_YoY5	5 Year over 5 Year
5271	TMFGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5272	TMFGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5273	TMFGX.Volume_SmoothDer	Derivative of Smoothed
5274	TMFGX.Volume_Log	Log of
5275	TMFGX.Volume_mva365	365 Day MA
5276	TMFGX.Volume_mva200	200 Day MA
5277	TMFGX.Volume_mva050	50 Day MA
5278	TMFGX.Adjusted_YoY	Year over Year
5284	TMFGX.Adjusted_Log	Log of
5285	TMFGX.Adjusted_mva365	365 Day MA
5286	TMFGX.Adjusted_mva200	200 Day MA
5287	TMFGX.Adjusted_mva050	50 Day MA
5328	IWM.Volume_YoY	Year over Year
5329	IWM.Volume_YoY4	4 Year over 4 Year
5331	IWM.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5332	IWM.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5333	IWM.Volume_SmoothDer	Derivative of Smoothed
5334	IWM.Volume_Log	Log of
5337	IWM.Volume_mva050	50 Day MA
5388	ONEQ.Volume_YoY	Year over Year
5391	ONEQ.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5392	ONEQ.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5393	ONEQ.Volume_SmoothDer	Derivative of Smoothed
5394	ONEQ.Volume_Log	Log of
5395	ONEQ.Volume_mva365	365 Day MA
5396	ONEQ.Volume_mva200	200 Day MA
5397	ONEQ.Volume_mva050	50 Day MA
5448	FSMAX.Volume_YoY	Year over Year
5449	FSMAX.Volume_YoY4	4 Year over 4 Year
5450	FSMAX.Volume_YoY5	5 Year over 5 Year
5451	FSMAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5452	FSMAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5453	FSMAX.Volume_SmoothDer	Derivative of Smoothed
5454	FSMAX.Volume_Log	Log of
5455	FSMAX.Volume_mva365	365 Day MA
5456	FSMAX.Volume_mva200	200 Day MA
5457	FSMAX.Volume_mva050	50 Day MA
5475	FXNAX.Open_mva365	365 Day MA
5485	FXNAX.High_mva365	365 Day MA
5495	FXNAX.Low_mva365	365 Day MA
5505	FXNAX.Close_mva365	365 Day MA
5508	FXNAX.Volume_YoY	Year over Year
5509	FXNAX.Volume_YoY4	4 Year over 4 Year
5510	FXNAX.Volume_YoY5	5 Year over 5 Year
5511	FXNAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5512	FXNAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5513	FXNAX.Volume_SmoothDer	Derivative of Smoothed
5514	FXNAX.Volume_Log	Log of
5515	FXNAX.Volume_mva365	365 Day MA
5516	FXNAX.Volume_mva200	200 Day MA
5517	FXNAX.Volume_mva050	50 Day MA
5521	FXNAX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5524	FXNAX.Adjusted_Log	Log of
5525	FXNAX.Adjusted_mva365	365 Day MA
5531	HAINX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5533	HAINX.Open_SmoothDer	Derivative of Smoothed
5541	HAINX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5543	HAINX.High_SmoothDer	Derivative of Smoothed
5551	HAINX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5553	HAINX.Low_SmoothDer	Derivative of Smoothed
5561	HAINX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5563	HAINX.Close_SmoothDer	Derivative of Smoothed
5568	HAINX.Volume_YoY	Year over Year
5569	HAINX.Volume_YoY4	4 Year over 4 Year
5570	HAINX.Volume_YoY5	5 Year over 5 Year
5571	HAINX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5572	HAINX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5573	HAINX.Volume_SmoothDer	Derivative of Smoothed
5574	HAINX.Volume_Log	Log of
5575	HAINX.Volume_mva365	365 Day MA
5576	HAINX.Volume_mva200	200 Day MA
5577	HAINX.Volume_mva050	50 Day MA
5581	HAINX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5583	HAINX.Adjusted_SmoothDer	Derivative of Smoothed
5585	HAINX.Adjusted_mva365	365 Day MA
5628	HNACX.Volume_YoY	Year over Year
5629	HNACX.Volume_YoY4	4 Year over 4 Year
5630	HNACX.Volume_YoY5	5 Year over 5 Year
5631	HNACX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5632	HNACX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5633	HNACX.Volume_SmoothDer	Derivative of Smoothed
5634	HNACX.Volume_Log	Log of
5635	HNACX.Volume_mva365	365 Day MA
5636	HNACX.Volume_mva200	200 Day MA
5637	HNACX.Volume_mva050	50 Day MA
5651	VEU.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5653	VEU.Open_SmoothDer	Derivative of Smoothed
5661	VEU.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5663	VEU.High_SmoothDer	Derivative of Smoothed
5671	VEU.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5681	VEU.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5692	VEU.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5693	VEU.Volume_SmoothDer	Derivative of Smoothed
5695	VEU.Volume_mva365	365 Day MA
5696	VEU.Volume_mva200	200 Day MA
5701	VEU.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5703	VEU.Adjusted_SmoothDer	Derivative of Smoothed
5748	VEIRX.Volume_YoY	Year over Year
5749	VEIRX.Volume_YoY4	4 Year over 4 Year
5750	VEIRX.Volume_YoY5	5 Year over 5 Year
5751	VEIRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5752	VEIRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5753	VEIRX.Volume_SmoothDer	Derivative of Smoothed
5754	VEIRX.Volume_Log	Log of
5755	VEIRX.Volume_mva365	365 Day MA
5756	VEIRX.Volume_mva200	200 Day MA
5757	VEIRX.Volume_mva050	50 Day MA
5765	VEIRX.Adjusted_mva365	365 Day MA
5773	BIL.Open_SmoothDer	Derivative of Smoothed
5783	BIL.High_SmoothDer	Derivative of Smoothed
5793	BIL.Low_SmoothDer	Derivative of Smoothed
5803	BIL.Close_SmoothDer	Derivative of Smoothed
5808	BIL.Volume_YoY	Year over Year
5811	BIL.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5812	BIL.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5813	BIL.Volume_SmoothDer	Derivative of Smoothed
5814	BIL.Volume_Log	Log of
5815	BIL.Volume_mva365	365 Day MA
5816	BIL.Volume_mva200	200 Day MA
5817	BIL.Volume_mva050	50 Day MA
5821	BIL.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5822	BIL.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5824	BIL.Adjusted_Log	Log of
5825	BIL.Adjusted_mva365	365 Day MA
5826	BIL.Adjusted_mva200	200 Day MA
5827	BIL.Adjusted_mva050	50 Day MA
5871	IVOO.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5872	IVOO.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5873	IVOO.Volume_SmoothDer	Derivative of Smoothed
5874	IVOO.Volume_Log	Log of
5875	IVOO.Volume_mva365	365 Day MA
5876	IVOO.Volume_mva200	200 Day MA
5877	IVOO.Volume_mva050	50 Day MA
5929	VO.Volume_YoY4	4 Year over 4 Year
5931	VO.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5932	VO.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5933	VO.Volume_SmoothDer	Derivative of Smoothed
5934	VO.Volume_Log	Log of
5935	VO.Volume_mva365	365 Day MA
5936	VO.Volume_mva200	200 Day MA
5937	VO.Volume_mva050	50 Day MA
5991	CZA.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5993	CZA.Volume_SmoothDer	Derivative of Smoothed
5994	CZA.Volume_Log	Log of
6015	VYM.Open_mva365	365 Day MA
6025	VYM.High_mva365	365 Day MA
6048	VYM.Volume_YoY	Year over Year
6051	VYM.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6052	VYM.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
6053	VYM.Volume_SmoothDer	Derivative of Smoothed
6054	VYM.Volume_Log	Log of
6055	VYM.Volume_mva365	365 Day MA
6056	VYM.Volume_mva200	200 Day MA
6065	VYM.Adjusted_mva365	365 Day MA
6075	ACWI.Open_mva365	365 Day MA
6085	ACWI.High_mva365	365 Day MA
6111	ACWI.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6112	ACWI.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
6113	ACWI.Volume_SmoothDer	Derivative of Smoothed
6116	ACWI.Volume_mva200	200 Day MA
6128	SLY.Open_YoY	Year over Year
6134	SLY.Open_Log	Log of
6135	SLY.Open_mva365	365 Day MA
6136	SLY.Open_mva200	200 Day MA
6137	SLY.Open_mva050	50 Day MA
6138	SLY.High_YoY	Year over Year
6144	SLY.High_Log	Log of
6145	SLY.High_mva365	365 Day MA
6146	SLY.High_mva200	200 Day MA
6147	SLY.High_mva050	50 Day MA
6148	SLY.Low_YoY	Year over Year
6154	SLY.Low_Log	Log of
6155	SLY.Low_mva365	365 Day MA
6156	SLY.Low_mva200	200 Day MA
6157	SLY.Low_mva050	50 Day MA
6158	SLY.Close_YoY	Year over Year
6164	SLY.Close_Log	Log of
6165	SLY.Close_mva365	365 Day MA
6166	SLY.Close_mva200	200 Day MA
6167	SLY.Close_mva050	50 Day MA
6168	SLY.Volume_YoY	Year over Year
6174	SLY.Volume_Log	Log of
6175	SLY.Volume_mva365	365 Day MA
6176	SLY.Volume_mva200	200 Day MA
6177	SLY.Volume_mva050	50 Day MA
6178	SLY.Adjusted_YoY	Year over Year
6184	SLY.Adjusted_Log	Log of
6185	SLY.Adjusted_mva365	365 Day MA
6186	SLY.Adjusted_mva200	200 Day MA
6187	SLY.Adjusted_mva050	50 Day MA
6228	QQQ.Volume_YoY	Year over Year
6229	QQQ.Volume_YoY4	4 Year over 4 Year
6231	QQQ.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6232	QQQ.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
6233	QQQ.Volume_SmoothDer	Derivative of Smoothed
6234	QQQ.Volume_Log	Log of
6237	QQQ.Volume_mva050	50 Day MA
6291	HYMB.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6293	HYMB.Volume_SmoothDer	Derivative of Smoothed
6294	HYMB.Volume_Log	Log of
6296	HYMB.Volume_mva200	200 Day MA
6305	HYMB.Adjusted_mva365	365 Day MA
6311	GOLD.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6314	GOLD.Open_Log	Log of
6315	GOLD.Open_mva365	365 Day MA
6321	GOLD.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6325	GOLD.High_mva365	365 Day MA
6331	GOLD.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6335	GOLD.Low_mva365	365 Day MA
6341	GOLD.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6351	GOLD.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6352	GOLD.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
6353	GOLD.Volume_SmoothDer	Derivative of Smoothed
6354	GOLD.Volume_Log	Log of
6356	GOLD.Volume_mva200	200 Day MA
6361	GOLD.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6365	GOLD.Adjusted_mva365	365 Day MA
6374	BKR.Open_Log	Log of
6375	BKR.Open_mva365	365 Day MA
6376	BKR.Open_mva200	200 Day MA
6385	BKR.High_mva365	365 Day MA
6386	BKR.High_mva200	200 Day MA
6395	BKR.Low_mva365	365 Day MA
6405	BKR.Close_mva365	365 Day MA
6408	BKR.Volume_YoY	Year over Year
6411	BKR.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6412	BKR.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
6413	BKR.Volume_SmoothDer	Derivative of Smoothed
6414	BKR.Volume_Log	Log of
6416	BKR.Volume_mva200	200 Day MA
6417	BKR.Volume_mva050	50 Day MA
6425	BKR.Adjusted_mva365	365 Day MA
6433	SLB.Open_SmoothDer	Derivative of Smoothed
6443	SLB.High_SmoothDer	Derivative of Smoothed
6453	SLB.Low_SmoothDer	Derivative of Smoothed
6463	SLB.Close_SmoothDer	Derivative of Smoothed
6471	SLB.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6472	SLB.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
6473	SLB.Volume_SmoothDer	Derivative of Smoothed
6475	SLB.Volume_mva365	365 Day MA
6476	SLB.Volume_mva200	200 Day MA
6477	SLB.Volume_mva050	50 Day MA
6483	SLB.Adjusted_SmoothDer	Derivative of Smoothed
6493	HAL.Open_SmoothDer	Derivative of Smoothed
6494	HAL.Open_Log	Log of
6503	HAL.High_SmoothDer	Derivative of Smoothed
6513	HAL.Low_SmoothDer	Derivative of Smoothed
6523	HAL.Close_SmoothDer	Derivative of Smoothed
6531	HAL.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6533	HAL.Volume_SmoothDer	Derivative of Smoothed
6534	HAL.Volume_Log	Log of
6535	HAL.Volume_mva365	365 Day MA
6536	HAL.Volume_mva200	200 Day MA
6537	HAL.Volume_mva050	50 Day MA
6543	HAL.Adjusted_SmoothDer	Derivative of Smoothed
6554	IP.Open_Log	Log of
6555	IP.Open_mva365	365 Day MA
6565	IP.High_mva365	365 Day MA
6575	IP.Low_mva365	365 Day MA
6585	IP.Close_mva365	365 Day MA
6591	IP.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6593	IP.Volume_SmoothDer	Derivative of Smoothed
6596	IP.Volume_mva200	200 Day MA
6605	IP.Adjusted_mva365	365 Day MA
6651	PKG.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6652	PKG.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
6653	PKG.Volume_SmoothDer	Derivative of Smoothed
6655	PKG.Volume_mva365	365 Day MA
6656	PKG.Volume_mva200	200 Day MA
6657	PKG.Volume_mva050	50 Day MA
6711	UPS.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6713	UPS.Volume_SmoothDer	Derivative of Smoothed
6715	UPS.Volume_mva365	365 Day MA
6716	UPS.Volume_mva200	200 Day MA
6771	FDX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6773	FDX.Volume_SmoothDer	Derivative of Smoothed
6777	FDX.Volume_mva050	50 Day MA
6791	T.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6793	T.Open_SmoothDer	Derivative of Smoothed
6794	T.Open_Log	Log of
6795	T.Open_mva365	365 Day MA
6796	T.Open_mva200	200 Day MA
6797	T.Open_mva050	50 Day MA
6801	T.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6803	T.High_SmoothDer	Derivative of Smoothed
6805	T.High_mva365	365 Day MA
6806	T.High_mva200	200 Day MA
6807	T.High_mva050	50 Day MA
6811	T.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6813	T.Low_SmoothDer	Derivative of Smoothed
6815	T.Low_mva365	365 Day MA
6816	T.Low_mva200	200 Day MA
6817	T.Low_mva050	50 Day MA
6821	T.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6823	T.Close_SmoothDer	Derivative of Smoothed
6825	T.Close_mva365	365 Day MA
6826	T.Close_mva200	200 Day MA
6827	T.Close_mva050	50 Day MA
6831	T.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6832	T.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
6833	T.Volume_SmoothDer	Derivative of Smoothed
6835	T.Volume_mva365	365 Day MA
6836	T.Volume_mva200	200 Day MA
6837	T.Volume_mva050	50 Day MA
6841	T.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6843	T.Adjusted_SmoothDer	Derivative of Smoothed
6845	T.Adjusted_mva365	365 Day MA
6846	T.Adjusted_mva200	200 Day MA
6847	T.Adjusted_mva050	50 Day MA
6851	VZ.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6853	VZ.Open_SmoothDer	Derivative of Smoothed
6855	VZ.Open_mva365	365 Day MA
6856	VZ.Open_mva200	200 Day MA
6857	VZ.Open_mva050	50 Day MA
6861	VZ.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6863	VZ.High_SmoothDer	Derivative of Smoothed
6865	VZ.High_mva365	365 Day MA
6866	VZ.High_mva200	200 Day MA
6867	VZ.High_mva050	50 Day MA
6871	VZ.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6873	VZ.Low_SmoothDer	Derivative of Smoothed
6875	VZ.Low_mva365	365 Day MA
6881	VZ.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6883	VZ.Close_SmoothDer	Derivative of Smoothed
6885	VZ.Close_mva365	365 Day MA
6887	VZ.Close_mva050	50 Day MA
6891	VZ.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6892	VZ.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
6893	VZ.Volume_SmoothDer	Derivative of Smoothed
6895	VZ.Volume_mva365	365 Day MA
6896	VZ.Volume_mva200	200 Day MA
6897	VZ.Volume_mva050	50 Day MA
6901	VZ.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6903	VZ.Adjusted_SmoothDer	Derivative of Smoothed
6905	VZ.Adjusted_mva365	365 Day MA
6906	VZ.Adjusted_mva200	200 Day MA
6907	VZ.Adjusted_mva050	50 Day MA
6908	PETA103600001M_YoY	U.S. Total Gasoline Retail Sales by Refiners, Monthly Year over Year
6914	PETA103600001M_Log	Log of U.S. Total Gasoline Retail Sales by Refiners, Monthly
6915	PETA103600001M_mva365	U.S. Total Gasoline Retail Sales by Refiners, Monthly 365 Day MA
6916	PETA103600001M_mva200	U.S. Total Gasoline Retail Sales by Refiners, Monthly 200 Day MA
6917	PETA103600001M_mva050	U.S. Total Gasoline Retail Sales by Refiners, Monthly 50 Day MA
6918	PETA123600001M_YoY	U.S. Regular Gasoline Retail Sales by Refiners, Monthly Year over Year
6924	PETA123600001M_Log	Log of U.S. Regular Gasoline Retail Sales by Refiners, Monthly
6925	PETA123600001M_mva365	U.S. Regular Gasoline Retail Sales by Refiners, Monthly 365 Day MA
6926	PETA123600001M_mva200	U.S. Regular Gasoline Retail Sales by Refiners, Monthly 200 Day MA
6927	PETA123600001M_mva050	U.S. Regular Gasoline Retail Sales by Refiners, Monthly 50 Day MA
6928	PETA143B00001M_YoY	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly Year over Year
6929	PETA143B00001M_YoY4	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 4 Year over 4 Year
6930	PETA143B00001M_YoY5	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 5 Year over 5 Year
6934	PETA143B00001M_Log	Log of U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
6935	PETA143B00001M_mva365	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 365 Day MA
6936	PETA143B00001M_mva200	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 200 Day MA
6937	PETA143B00001M_mva050	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 50 Day MA
6938	PETA133B00001M_YoY	U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly Year over Year
6940	PETA133B00001M_YoY5	U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 5 Year over 5 Year
6944	PETA133B00001M_Log	Log of U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly
6945	PETA133B00001M_mva365	U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 365 Day MA
6946	PETA133B00001M_mva200	U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 200 Day MA
6947	PETA133B00001M_mva050	U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 50 Day MA
6948	TOTALOGNRPUSM_YoY	Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly Year over Year
6950	TOTALOGNRPUSM_YoY5	Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 5 Year over 5 Year
6953	TOTALOGNRPUSM_SmoothDer	Derivative of Smoothed Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
6954	TOTALOGNRPUSM_Log	Log of Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
6957	TOTALOGNRPUSM_mva050	Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 50 Day MA
6960	TOTALPANRPUSM_YoY5	Crude Oil Rotary Rigs in Operation, Monthly 5 Year over 5 Year
6963	TOTALPANRPUSM_SmoothDer	Derivative of Smoothed Crude Oil Rotary Rigs in Operation, Monthly
6964	TOTALPANRPUSM_Log	Log of Crude Oil Rotary Rigs in Operation, Monthly
6967	TOTALPANRPUSM_mva050	Crude Oil Rotary Rigs in Operation, Monthly 50 Day MA
6968	TOTALNGNRPUSM_YoY	Natural Gas Rotary Rigs in Operation, Monthly Year over Year
6970	TOTALNGNRPUSM_YoY5	Natural Gas Rotary Rigs in Operation, Monthly 5 Year over 5 Year
6976	TOTALNGNRPUSM_mva200	Natural Gas Rotary Rigs in Operation, Monthly 200 Day MA
6978	BKRTotal_YoY	Total Rig Count Year over Year
6980	BKRTotal_YoY5	Total Rig Count 5 Year over 5 Year
6984	BKRTotal_Log	Log of Total Rig Count
6985	BKRTotal_mva365	Total Rig Count 365 Day MA
6986	BKRTotal_mva200	Total Rig Count 200 Day MA
6987	BKRTotal_mva050	Total Rig Count 50 Day MA
6988	BKRGas_YoY	Gas Rig Count Year over Year
6990	BKRGas_YoY5	Gas Rig Count 5 Year over 5 Year
6994	BKRGas_Log	Log of Gas Rig Count
6995	BKRGas_mva365	Gas Rig Count 365 Day MA
6996	BKRGas_mva200	Gas Rig Count 200 Day MA
6997	BKRGas_mva050	Gas Rig Count 50 Day MA
6998	BKROil_YoY	Oil Rig Count Year over Year
7000	BKROil_YoY5	Oil Rig Count 5 Year over 5 Year
7004	BKROil_Log	Log of Oil Rig Count
7005	BKROil_mva365	Oil Rig Count 365 Day MA
7006	BKROil_mva200	Oil Rig Count 200 Day MA
7007	BKROil_mva050	Oil Rig Count 50 Day MA
7008	FARMINCOME_YoY	Net Farm Income Year over Year
7009	FARMINCOME_YoY4	Net Farm Income 4 Year over 4 Year
7010	FARMINCOME_YoY5	Net Farm Income 5 Year over 5 Year
7014	FARMINCOME_Log	Log of Net Farm Income
7015	FARMINCOME_mva365	Net Farm Income 365 Day MA
7016	FARMINCOME_mva200	Net Farm Income 200 Day MA
7017	FARMINCOME_mva050	Net Farm Income 50 Day MA
7018	OPEARNINGSPERSHARE_YoY	Operating Earnings per Share Year over Year
7024	OPEARNINGSPERSHARE_Log	Log of Operating Earnings per Share
7025	OPEARNINGSPERSHARE_mva365	Operating Earnings per Share 365 Day MA
7026	OPEARNINGSPERSHARE_mva200	Operating Earnings per Share 200 Day MA
7027	OPEARNINGSPERSHARE_mva050	Operating Earnings per Share 50 Day MA
7028	AREARNINGSPERSHARE_YoY	As-Reported Earnings per Share Year over Year
7034	AREARNINGSPERSHARE_Log	Log of As-Reported Earnings per Share
7035	AREARNINGSPERSHARE_mva365	As-Reported Earnings per Share 365 Day MA
7036	AREARNINGSPERSHARE_mva200	As-Reported Earnings per Share 200 Day MA
7037	AREARNINGSPERSHARE_mva050	As-Reported Earnings per Share 50 Day MA
7038	CASHDIVIDENDSPERSHR_YoY	Cash Dividends per Share Year over Year
7044	CASHDIVIDENDSPERSHR_Log	Log of Cash Dividends per Share
7045	CASHDIVIDENDSPERSHR_mva365	Cash Dividends per Share 365 Day MA
7046	CASHDIVIDENDSPERSHR_mva200	Cash Dividends per Share 200 Day MA
7047	CASHDIVIDENDSPERSHR_mva050	Cash Dividends per Share 50 Day MA
7048	SALESPERSHR_YoY	Sales per Share Year over Year
7050	SALESPERSHR_YoY5	Sales per Share 5 Year over 5 Year
7054	SALESPERSHR_Log	Log of Sales per Share
7055	SALESPERSHR_mva365	Sales per Share 365 Day MA
7056	SALESPERSHR_mva200	Sales per Share 200 Day MA
7057	SALESPERSHR_mva050	Sales per Share 50 Day MA
7058	BOOKVALPERSHR_YoY	Book value per Share Year over Year
7064	BOOKVALPERSHR_Log	Log of Book value per Share
7065	BOOKVALPERSHR_mva365	Book value per Share 365 Day MA
7066	BOOKVALPERSHR_mva200	Book value per Share 200 Day MA
7067	BOOKVALPERSHR_mva050	Book value per Share 50 Day MA
7068	CAPEXPERSHR_YoY	Cap ex per Share Year over Year
7070	CAPEXPERSHR_YoY5	Cap ex per Share 5 Year over 5 Year
7074	CAPEXPERSHR_Log	Log of Cap ex per Share
7075	CAPEXPERSHR_mva365	Cap ex per Share 365 Day MA
7076	CAPEXPERSHR_mva200	Cap ex per Share 200 Day MA
7077	CAPEXPERSHR_mva050	Cap ex per Share 50 Day MA
7078	PRICE_YoY	Price Year over Year
7084	PRICE_Log	Log of Price
7085	PRICE_mva365	Price 365 Day MA
7086	PRICE_mva200	Price 200 Day MA
7087	PRICE_mva050	Price 50 Day MA
7088	OPEARNINGSTTM_YoY	TTM Operating Earnings Year over Year
7090	OPEARNINGSTTM_YoY5	TTM Operating Earnings 5 Year over 5 Year
7094	OPEARNINGSTTM_Log	Log of TTM Operating Earnings
7095	OPEARNINGSTTM_mva365	TTM Operating Earnings 365 Day MA
7096	OPEARNINGSTTM_mva200	TTM Operating Earnings 200 Day MA
7097	OPEARNINGSTTM_mva050	TTM Operating Earnings 50 Day MA
7098	AREARNINGSTTM_YoY	TTM Reported Earnings Year over Year
7100	AREARNINGSTTM_YoY5	TTM Reported Earnings 5 Year over 5 Year
7104	AREARNINGSTTM_Log	Log of TTM Reported Earnings
7105	AREARNINGSTTM_mva365	TTM Reported Earnings 365 Day MA
7106	AREARNINGSTTM_mva200	TTM Reported Earnings 200 Day MA
7107	AREARNINGSTTM_mva050	TTM Reported Earnings 50 Day MA
7108	FINRAMarginDebt_YoY	Margin Debt Year over Year
7114	FINRAMarginDebt_Log	Log of Margin Debt
7115	FINRAMarginDebt_mva365	Margin Debt 365 Day MA
7116	FINRAMarginDebt_mva200	Margin Debt 200 Day MA
7117	FINRAMarginDebt_mva050	Margin Debt 50 Day MA
7118	FINRAFreeCreditMargin_YoY	Free Credit Balances in Customers’ Securities Margin Accounts Year over Year
7124	FINRAFreeCreditMargin_Log	Log of Free Credit Balances in Customers’ Securities Margin Accounts
7125	FINRAFreeCreditMargin_mva365	Free Credit Balances in Customers’ Securities Margin Accounts 365 Day MA
7126	FINRAFreeCreditMargin_mva200	Free Credit Balances in Customers’ Securities Margin Accounts 200 Day MA
7127	FINRAFreeCreditMargin_mva050	Free Credit Balances in Customers’ Securities Margin Accounts 50 Day MA
7128	OCCEquityVolume_YoY	Equity Options Volume Year over Year
7129	OCCEquityVolume_YoY4	Equity Options Volume 4 Year over 4 Year
7130	OCCEquityVolume_YoY5	Equity Options Volume 5 Year over 5 Year
7134	OCCEquityVolume_Log	Log of Equity Options Volume
7135	OCCEquityVolume_mva365	Equity Options Volume 365 Day MA
7136	OCCEquityVolume_mva200	Equity Options Volume 200 Day MA
7137	OCCEquityVolume_mva050	Equity Options Volume 50 Day MA
7138	OCCNonEquityVolume_YoY	Non-Equity Options Volume Year over Year
7139	OCCNonEquityVolume_YoY4	Non-Equity Options Volume 4 Year over 4 Year
7140	OCCNonEquityVolume_YoY5	Non-Equity Options Volume 5 Year over 5 Year
7144	OCCNonEquityVolume_Log	Log of Non-Equity Options Volume
7145	OCCNonEquityVolume_mva365	Non-Equity Options Volume 365 Day MA
7146	OCCNonEquityVolume_mva200	Non-Equity Options Volume 200 Day MA
7147	OCCNonEquityVolume_mva050	Non-Equity Options Volume 50 Day MA
7155	RSALESAGG_mva365	Real Retail and Food Services Sales (RRSFS and RSALES) 365 Day MA
7164	BUSLOANS.minus.BUSLOANSNSA_Log	Log of Business Loans (Montlhy) SA - NSA
7165	BUSLOANS.minus.BUSLOANSNSA_mva365	Business Loans (Montlhy) SA - NSA 365 Day MA
7174	BUSLOANS.minus.BUSLOANSNSA.by.GDP_Log	Log of Business Loans (Montlhy) SA - NSA divided by GDP
7175	BUSLOANS.minus.BUSLOANSNSA.by.GDP_mva365	Business Loans (Montlhy) SA - NSA divided by GDP 365 Day MA
7178	BUSLOANS.by.GDP_YoY	Business Loans Normalized by GDP Year over Year
7179	BUSLOANS.by.GDP_YoY4	Business Loans Normalized by GDP 4 Year over 4 Year
7193	BUSLOANS.INTEREST_SmoothDer	Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burdens
7196	BUSLOANS.INTEREST_mva200	Business Loans (Monthly, SA) Adjusted Interest Burdens 200 Day MA
7203	BUSLOANS.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
7206	BUSLOANS.INTEREST.by.GDP_mva200	Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 200 Day MA
7208	BUSLOANSNSA.by.GDP_YoY	Business Loans Normalized by GDP Year over Year
7209	BUSLOANSNSA.by.GDP_YoY4	Business Loans Normalized by GDP 4 Year over 4 Year
7213	BUSLOANSNSA.by.GDP_SmoothDer	Derivative of Smoothed Business Loans Normalized by GDP
7217	BUSLOANSNSA.by.GDP_mva050	Business Loans Normalized by GDP 50 Day MA
7218	TOTCI.by.GDP_YoY	Business Loans (Weekly, SA) Normalized by GDP Year over Year
7219	TOTCI.by.GDP_YoY4	Business Loans (Weekly, SA) Normalized by GDP 4 Year over 4 Year
7228	TOTCINSA.by.GDP_YoY	Business Loans (Weekly, NSA) Normalized by GDP Year over Year
7229	TOTCINSA.by.GDP_YoY4	Business Loans (Weekly, NSA) Normalized by GDP 4 Year over 4 Year
7231	TOTCINSA.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Normalized by GDP
7233	TOTCINSA.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (Weekly, NSA) Normalized by GDP
7237	TOTCINSA.by.GDP_mva050	Business Loans (Weekly, NSA) Normalized by GDP 50 Day MA
7243	TOTCINSA.INTEREST_SmoothDer	Derivative of Smoothed Business Loans (Weekly, NSA) Adjusted Interest Burdens
7246	TOTCINSA.INTEREST_mva200	Business Loans (Weekly, NSA) Adjusted Interest Burdens 200 Day MA
7253	TOTCINSA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
7256	TOTCINSA.INTEREST.by.GDP_mva200	Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 200 Day MA
7258	W875RX1.by.GDP_YoY	Real Personal Income Normalized by GDP Year over Year
7259	W875RX1.by.GDP_YoY4	Real Personal Income Normalized by GDP 4 Year over 4 Year
7261	W875RX1.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Personal Income Normalized by GDP
7263	W875RX1.by.GDP_SmoothDer	Derivative of Smoothed Real Personal Income Normalized by GDP
7264	W875RX1.by.GDP_Log	Log of Real Personal Income Normalized by GDP
7267	W875RX1.by.GDP_mva050	Real Personal Income Normalized by GDP 50 Day MA
7268	A065RC1A027NBEA.by.GDP_YoY	Personal Income (NSA) Normalized by GDP Year over Year
7269	A065RC1A027NBEA.by.GDP_YoY4	Personal Income (NSA) Normalized by GDP 4 Year over 4 Year
7273	A065RC1A027NBEA.by.GDP_SmoothDer	Derivative of Smoothed Personal Income (NSA) Normalized by GDP
7274	A065RC1A027NBEA.by.GDP_Log	Log of Personal Income (NSA) Normalized by GDP
7278	PI.by.GDP_YoY	Personal Income (SA) Normalized by GDP Year over Year
7281	PI.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Personal Income (SA) Normalized by GDP
7283	PI.by.GDP_SmoothDer	Derivative of Smoothed Personal Income (SA) Normalized by GDP
7284	PI.by.GDP_Log	Log of Personal Income (SA) Normalized by GDP
7285	PI.by.GDP_mva365	Personal Income (SA) Normalized by GDP 365 Day MA
7286	PI.by.GDP_mva200	Personal Income (SA) Normalized by GDP 200 Day MA
7287	PI.by.GDP_mva050	Personal Income (SA) Normalized by GDP 50 Day MA
7294	A053RC1Q027SBEA.by.GDP_Log	Log of National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
7295	A053RC1Q027SBEA.by.GDP_mva365	National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP 365 Day MA
7296	A053RC1Q027SBEA.by.GDP_mva200	National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP 200 Day MA
7297	A053RC1Q027SBEA.by.GDP_mva050	National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP 50 Day MA
7304	CPROFIT.by.GDP_Log	Log of National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
7305	CPROFIT.by.GDP_mva365	National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP 365 Day MA
7306	CPROFIT.by.GDP_mva200	National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP 200 Day MA
7307	CPROFIT.by.GDP_mva050	National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP 50 Day MA
7308	CONSUMERNSA.by.GDP_YoY	Consumer Loans Not Seasonally Adjusted divided by GDP Year over Year
7318	RREACBM027NBOG.by.GDP_YoY	Residental Real Estate Loans (Monthly, NSA) divided by GDP Year over Year
7319	RREACBM027NBOG.by.GDP_YoY4	Residental Real Estate Loans (Monthly, NSA) divided by GDP 4 Year over 4 Year
7323	RREACBM027NBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Monthly, NSA) divided by GDP
7328	RREACBM027SBOG.by.GDP_YoY	Residental Real Estate Loans (Monthly, SA) divided by GDP Year over Year
7329	RREACBM027SBOG.by.GDP_YoY4	Residental Real Estate Loans (Monthly, SA) divided by GDP 4 Year over 4 Year
7331	RREACBM027SBOG.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, SA) divided by GDP
7333	RREACBM027SBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Monthly, SA) divided by GDP
7334	RREACBM027SBOG.by.GDP_Log	Log of Residental Real Estate Loans (Monthly, SA) divided by GDP
7337	RREACBM027SBOG.by.GDP_mva050	Residental Real Estate Loans (Monthly, SA) divided by GDP 50 Day MA
7338	RREACBW027SBOG.by.GDP_YoY	Residental Real Estate Loans (Weekly, SA) divided by GDP Year over Year
7341	RREACBW027SBOG.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, SA) divided by GDP
7343	RREACBW027SBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Weekly, SA) divided by GDP
7344	RREACBW027SBOG.by.GDP_Log	Log of Residental Real Estate Loans (Weekly, SA) divided by GDP
7347	RREACBW027SBOG.by.GDP_mva050	Residental Real Estate Loans (Weekly, SA) divided by GDP 50 Day MA
7371	DGORDER.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Durable Goods (Monthly, NSA) divided by GDP
7373	DGORDER.by.GDP_SmoothDer	Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
7374	DGORDER.by.GDP_Log	Log of Durable Goods (Monthly, NSA) divided by GDP
7377	DGORDER.by.GDP_mva050	Durable Goods (Monthly, NSA) divided by GDP 50 Day MA
7378	ASHMA.by.GDP_YoY	Home Mortgages (Quarterly, NSA) divided by GDP Year over Year
7383	ASHMA.by.GDP_SmoothDer	Derivative of Smoothed Home Mortgages (Quarterly, NSA) divided by GDP
7384	ASHMA.by.GDP_Log	Log of Home Mortgages (Quarterly, NSA) divided by GDP
7393	ASHMA.INTEREST_SmoothDer	Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7396	ASHMA.INTEREST_mva200	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
7403	ASHMA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
7410	CONSUMERNSA.INTEREST_YoY5	Consumer Loans (Not Seasonally Adjusted) Interest Burdens 5 Year over 5 Year
7418	CONSUMERNSA.INTEREST.by.GDP_YoY	Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP Year over Year
7435	TOTLNNSA_mva365	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 365 Day MA
7436	TOTLNNSA_mva200	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 200 Day MA
7438	TOTLNNSA.by.GDP_YoY	Total Loans Not Seasonally Adjusted divided by GDP Year over Year
7439	TOTLNNSA.by.GDP_YoY4	Total Loans Not Seasonally Adjusted divided by GDP 4 Year over 4 Year
7453	TOTLNNSA.INTEREST_SmoothDer	Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burdens
7456	TOTLNNSA.INTEREST_mva200	Total Loans Not Seasonally Adjusted Interest Burdens 200 Day MA
7463	TOTLNNSA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
7466	TOTLNNSA.INTEREST.by.GDP_mva200	Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 200 Day MA
7471	WRESBAL.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Reserve Balances with Federal Reserve Banks Divided by GDP
7473	WRESBAL.by.GDP_SmoothDer	Derivative of Smoothed Reserve Balances with Federal Reserve Banks Divided by GDP
7477	WRESBAL.by.GDP_mva050	Reserve Balances with Federal Reserve Banks Divided by GDP 50 Day MA
7478	EXCSRESNW.by.GDP_YoY	Excess Reserves of Depository Institutions Divided by GDP Year over Year
7479	EXCSRESNW.by.GDP_YoY4	Excess Reserves of Depository Institutions Divided by GDP 4 Year over 4 Year
7483	EXCSRESNW.by.GDP_SmoothDer	Derivative of Smoothed Excess Reserves of Depository Institutions Divided by GDP
7484	EXCSRESNW.by.GDP_Log	Log of Excess Reserves of Depository Institutions Divided by GDP
7511	EXPCH.minus.IMPCH_Smooth	Savitsky-Golay Smoothed (p=3, n=365) U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
7513	EXPCH.minus.IMPCH_SmoothDer	Derivative of Smoothed U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
7514	EXPCH.minus.IMPCH_Log	Log of U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
7516	EXPCH.minus.IMPCH_mva200	U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) 200 Day MA
7517	EXPCH.minus.IMPCH_mva050	U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) 50 Day MA
7521	EXPMX.minus.IMPMX_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
7523	EXPMX.minus.IMPMX_SmoothDer	Derivative of Smoothed
7524	EXPMX.minus.IMPMX_Log	Log of
7531	SRPSABSNNCB.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
7534	SRPSABSNNCB.by.GDP_Log	Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
7535	SRPSABSNNCB.by.GDP_mva365	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 365 Day MA
7538	ASTLL.by.GDP_YoY	All sectors; total loans; liability, Level (NSA) Divided by GDP Year over Year
7539	ASTLL.by.GDP_YoY4	All sectors; total loans; liability, Level (NSA) Divided by GDP 4 Year over 4 Year
7543	ASTLL.by.GDP_SmoothDer	Derivative of Smoothed All sectors; total loans; liability, Level (NSA) Divided by GDP
7544	ASTLL.by.GDP_Log	Log of All sectors; total loans; liability, Level (NSA) Divided by GDP
7548	ASFMA.by.GDP_YoY	All sectors; farm mortgages; asset, Level (NSA) Divided by GDP Year over Year
7553	ASFMA.by.GDP_SmoothDer	Derivative of Smoothed All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
7554	ASFMA.by.GDP_Log	Log of All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
7564	ASFMA.by.ASTLL_Log	Log of All sectors; total loans Divided by farm mortgages
7565	ASFMA.by.ASTLL_mva365	All sectors; total loans Divided by farm mortgages 365 Day MA
7566	ASFMA.by.ASTLL_mva200	All sectors; total loans Divided by farm mortgages 200 Day MA
7567	ASFMA.by.ASTLL_mva050	All sectors; total loans Divided by farm mortgages 50 Day MA
7573	ASFMA.INTEREST_SmoothDer	Derivative of Smoothed Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7576	ASFMA.INTEREST_mva200	Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
7583	ASFMA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
7588	FARMINCOME.by.GDP_YoY	Farm Income (Annual, NSA) Divided by GDP Year over Year
7589	FARMINCOME.by.GDP_YoY4	Farm Income (Annual, NSA) Divided by GDP 4 Year over 4 Year
7593	FARMINCOME.by.GDP_SmoothDer	Derivative of Smoothed Farm Income (Annual, NSA) Divided by GDP
7594	FARMINCOME.by.GDP_Log	Log of Farm Income (Annual, NSA) Divided by GDP
7598	BOGMBASE.by.GDP_YoY	BOGMBASE Divided by GDP Year over Year
7601	BOGMBASE.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) BOGMBASE Divided by GDP
7603	BOGMBASE.by.GDP_SmoothDer	Derivative of Smoothed BOGMBASE Divided by GDP
7608	WALCL.by.GDP_YoY	All Federal Reserve Banks: Total Assets Divided by GDP Year over Year
7613	WALCL.by.GDP_SmoothDer	Derivative of Smoothed All Federal Reserve Banks: Total Assets Divided by GDP
7618	ECBASSETS.by.EUNNGDP_YoY	Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP Year over Year
7619	ECBASSETS.by.EUNNGDP_YoY4	Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP 4 Year over 4 Year
7623	ECBASSETS.by.EUNNGDP_SmoothDer	Derivative of Smoothed Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
7624	ECBASSETS.by.EUNNGDP_Log	Log of Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
7631	DGS30TO10_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7632	DGS30TO10_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7634	DGS30TO10_Log	Log of Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7635	DGS30TO10_mva365	Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10) 365 Day MA
7636	DGS30TO10_mva200	Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10) 200 Day MA
7644	DGS10TO1_Log	Log of Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
7645	DGS10TO1_mva365	Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1) 365 Day MA
7646	DGS10TO1_mva200	Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1) 200 Day MA
7654	DGS10TO2_Log	Log of Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7655	DGS10TO2_mva365	Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2) 365 Day MA
7656	DGS10TO2_mva200	Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2) 200 Day MA
7664	DGS10TOTB3MS_Log	Log of Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7665	DGS10TOTB3MS_mva365	Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 365 Day MA
7666	DGS10TOTB3MS_mva200	Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 200 Day MA
7674	DGS10TODTB3_Log	Log of Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7675	DGS10TODTB3_mva365	Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3) 365 Day MA
7676	DGS10TODTB3_mva200	Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3) 200 Day MA
7681	DGS10ByAAA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) AAA ratio to 10 year treasury (AAA/DGS10)
7682	DGS10ByAAA_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) AAA ratio to 10 year treasury (AAA/DGS10)
7683	DGS10ByAAA_SmoothDer	Derivative of Smoothed AAA ratio to 10 year treasury (AAA/DGS10)
7684	DGS10ByAAA_Log	Log of AAA ratio to 10 year treasury (AAA/DGS10)
7689	LNU03000000BYPOPTHM_YoY4	Unemployment level (NSA) / Population 4 Year over 4 Year
7691	LNU03000000BYPOPTHM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Unemployment level (NSA) / Population
7693	LNU03000000BYPOPTHM_SmoothDer	Derivative of Smoothed Unemployment level (NSA) / Population
7695	LNU03000000BYPOPTHM_mva365	Unemployment level (NSA) / Population 365 Day MA
7696	LNU03000000BYPOPTHM_mva200	Unemployment level (NSA) / Population 200 Day MA
7699	UNEMPLOYBYPOPTHM_YoY4	Unemployment level, seasonally adjusted / Population 4 Year over 4 Year
7701	UNEMPLOYBYPOPTHM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Unemployment level, seasonally adjusted / Population
7705	UNEMPLOYBYPOPTHM_mva365	Unemployment level, seasonally adjusted / Population 365 Day MA
7707	UNEMPLOYBYPOPTHM_mva050	Unemployment level, seasonally adjusted / Population 50 Day MA
7708	NPPTTLBYPOPTHM_YoY	ADP Private Employment / Population Year over Year
7713	NPPTTLBYPOPTHM_SmoothDer	Derivative of Smoothed ADP Private Employment / Population
7721	U6toU3_Smooth	Savitsky-Golay Smoothed (p=3, n=365) U6RATE minums UNRATE
7723	U6toU3_SmoothDer	Derivative of Smoothed U6RATE minums UNRATE
7725	U6toU3_mva365	U6RATE minums UNRATE 365 Day MA
7726	U6toU3_mva200	U6RATE minums UNRATE 200 Day MA
7733	DCOILBRENTEU.by.PPIACO_SmoothDer	Derivative of Smoothed Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
7743	DCOILWTICO.by.PPIACO_SmoothDer	Derivative of Smoothed Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7744	DCOILWTICO.by.PPIACO_Log	Log of Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7754	GDP.by.GDPDEF_Log	Log of Nominal GDP Normalized by GDP def
7755	GDP.by.GDPDEF_mva365	Nominal GDP Normalized by GDP def 365 Day MA
7756	GDP.by.GDPDEF_mva200	Nominal GDP Normalized by GDP def 200 Day MA
7757	GDP.by.GDPDEF_mva050	Nominal GDP Normalized by GDP def 50 Day MA
7761	GSG.Close.by.GDPDEF_Smooth	Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by GDP def
7763	GSG.Close.by.GDPDEF_SmoothDer	Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by GDP def
7771	GSG.Close.by.GSPC.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by S&P 500
7772	GSG.Close.by.GSPC.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) GSCI Commodity-Indexed Trust, Normalized by S&P 500
7773	GSG.Close.by.GSPC.Close_SmoothDer	Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by S&P 500
7774	GSG.Close.by.GSPC.Close_Log	Log of GSCI Commodity-Indexed Trust, Normalized by S&P 500
7777	GSG.Close.by.GSPC.Close_mva050	GSCI Commodity-Indexed Trust, Normalized by S&P 500 50 Day MA
7785	GDPBYPOPTHM_mva365	GDP/Population 365 Day MA
7795	GDPBYCPIAUCSL_mva365	GDP divided by CPI 365 Day MA
7811	GSPC.CloseBYMDY.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365) GSPC by MDY
7813	GSPC.CloseBYMDY.Close_SmoothDer	Derivative of Smoothed GSPC by MDY
7815	GSPC.CloseBYMDY.Close_mva365	GSPC by MDY 365 Day MA
7816	GSPC.CloseBYMDY.Close_mva200	GSPC by MDY 200 Day MA
7817	GSPC.CloseBYMDY.Close_mva050	GSPC by MDY 50 Day MA
7821	QQQ.CloseBYMDY.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365) QQQ by MDY
7823	QQQ.CloseBYMDY.Close_SmoothDer	Derivative of Smoothed QQQ by MDY
7825	QQQ.CloseBYMDY.Close_mva365	QQQ by MDY 365 Day MA
7826	QQQ.CloseBYMDY.Close_mva200	QQQ by MDY 200 Day MA
7831	GSPC.DailySwing_Smooth	Savitsky-Golay Smoothed (p=3, n=365) S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
7832	GSPC.DailySwing_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
7833	GSPC.DailySwing_SmoothDer	Derivative of Smoothed S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
7834	GSPC.DailySwing_Log	Log of S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
7835	GSPC.DailySwing_mva365	S&P 500 (^GSPC) Daily Swing: (High - Low) / Open 365 Day MA
7836	GSPC.DailySwing_mva200	S&P 500 (^GSPC) Daily Swing: (High - Low) / Open 200 Day MA
7837	GSPC.DailySwing_mva050	S&P 500 (^GSPC) Daily Swing: (High - Low) / Open 50 Day MA
7845	GSPC.Open.by.GDPDEF_mva365	S&P 500 (^GSPC) Open divided by GDP deflator 365 Day MA
7865	HNFSUSNSA.minus.HSN1FNSA_mva365	Houses for sale - houses sold 365 Day MA
7866	HNFSUSNSA.minus.HSN1FNSA_mva200	Houses for sale - houses sold 200 Day MA
7871	MSPUS.times.HOUST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) New privately owned units start times median price
7876	MSPUS.times.HOUST_mva200	New privately owned units start times median price 200 Day MA
7877	MSPUS.times.HOUST_mva050	New privately owned units start times median price 50 Day MA
7881	HOUST.div.POPTHM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Housing starts divided by U.S. population
7886	HOUST.div.POPTHM_mva200	Housing starts divided by U.S. population 200 Day MA
7887	HOUST.div.POPTHM_mva050	Housing starts divided by U.S. population 50 Day MA
7890	MSPUS.times.HNFSUSNSA_YoY5	New privately owned 1-family units for sale times median price 5 Year over 5 Year
7895	MSPUS.times.HNFSUSNSA_mva365	New privately owned 1-family units for sale times median price 365 Day MA
7896	MSPUS.times.HNFSUSNSA_mva200	New privately owned 1-family units for sale times median price 200 Day MA
7898	MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S_YoY	Median home price times new and existing houses sold Year over Year
7906	MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S_mva200	Median home price times new and existing houses sold 200 Day MA
7907	MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S_mva050	Median home price times new and existing houses sold 50 Day MA
7908	MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S.by.GDP_YoY	New and existing home sales volume Year over Year
7916	MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S.by.GDP_mva200	New and existing home sales volume 200 Day MA
7917	MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S.by.GDP_mva050	New and existing home sales volume 50 Day MA
7919	TOTLLNSA.PLUS.WRESBAL	Total Loans Plus All Reserves (TOTLLNSA + WRESBAL)

Equities

S&P 500 SMA Trends

Take a look at recent activity in the equities market. This section looks at the S&P 500 close value to the 50 day and 200 day simple moving average (SMA).

This is a longer view for the S&P 500 trend.

Equity indexes normalized by GDP

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

The last two years compare favorably with the period around the late 1950’s. Need to dig into this one.

datay <- "GSPC.Close"
ylim <- c(2000, d.GSPC.max)
my.data <- plotSimilarPeriods(df.data, dfRecession, df.symbols, datay, ylim, i.window = 60)
my.data[[1]]

Look at how the different segments of the market move

datay <- "GSPC.CloseBYMDY.Close_YoY"
ylim <- c(-50, 75)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

datay <- "GSPC.CloseBYMDY.Close"
ylim <- c(0, 20)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

S&P 500 Normalized moving average

Look at moving average relationship by dividing the S&P 500 open price by the 200 day SMA.

datay <- "GSPC.Open_mva200_Norm"
ylim <- c(50, 125)
dt.start = as.Date('2008-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Crossovers

Look at the 50 DMA versus 200 DMA, often used as a technical indicator of market direction.

datay <- "GSPC.Open_mva050_mva200"
ylim <- c(-300, 300)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

datay <- "GSPC.Open_mva050_mva200_sig "
ylim <- c(0.0, 1.0)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

S&P 500 TTM P/E

Take a look at some of the earnings trends from SilverBlatt’s sheet.

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Take a longer look back at as-reported and operating earnings

Market prices can out-run earnings so take a look at price to earnings.

Focus on some of the more recent activity

S&P 500 Sales

{r SP500Sales } # # datay <- "MULTPLSP500SALESQUARTER" # ylim <- c(500, 2000) # dt.start <- as.Date('1999-01-01') # plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start) # #

{r SP500SalesShort } # # datay <- "MULTPLSP500SALESQUARTER" # ylim <- c(500, 2000) # dt.start = as.Date('2001-01-01') # plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start) # #

Unit Profits

The series peaks in the middle of a bull market.

S&P 500 dividends

12-month real dividend per share inflation adjusted November, 2018 dollars. Data courtesy Standard & Poor’s and Robert Shiller.

https://www.quandl.com/data/MULTPL/SP500_DIV_MONTH-S-P-500-Dividend-by-Month

Evaluate year over year dividend growth.

Real value dividend growth.

S&P 500 dividend yield (12 month dividend per share)/price. Yields following September 2018 (including the current yield) are estimated based on 12 month dividends through September 2018, as reported by S&P. Sources: Standard & Poor’s for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields.

https://www.quandl.com/data/MULTPL/SP500_DIV_YIELD_MONTH-S-P-500-Dividend-Yield-by-Month

# datay <- "MULTPLSP500DIVYIELDMONTH"
# ylim <- c(0, 12)
# dtStart = as.Date('1950-01-01')
# plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

# datay <- "MULTPLSP500DIVYIELDMONTH"
# ylim <- c(1, 4)
# dtStart = as.Date('2001-01-01')
# plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 Volume

The log of the S&P volume has some interesting patterns, but nothing that seems to help with a recession indicator.

That is one spiky data series. Not sure there is a lot to help us here.

Russell 2000

Take a look at recent activity in the small cap market.

S&P 500 to Rusell 2000

Thirty day movement

Correlation

## Warning in max.default(structure(numeric(0), class = "Date"),
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S&P 500 to MDY (Mid-cap) 2000 Correlation

datay1 <- "RLG.Open"
ylim1 <- c(0, 2500)

datay2 <- "MDY.Open"
ylim2 <- c(0, 500)

dtStart <- as.Date("1jan2003","%d%b%Y")

w <- 30
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

## Warning in max.default(structure(numeric(0), class = "Date"),
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## returning -Inf

## Warning in min.default(structure(numeric(0), class = "Date"),
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## returning Inf

Dividend Stocks

This is an interesting series, they should perform better through the recessions. Unfortunately they are short lived so there is not much data so this is more of a place holder for now.

datay <- "NOBL.Open"
ylim <- c(40, 110)
dt.start <- as.Date('2014-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Margin and option data

NYSE Margin Debt

Taking a look at margin debt. NYXDATA stopped providing NYSE margin debt data on Dec 2017. Data is available from FINRA, but it includes more accounts than the data did for NYXdata. I stitched togeter the data sets: data after Jan 2010 include NYSE+Others, data prior is just NYSE account data scaled up to match the FINRA data.

It tends to creep up when there is a frenzy in the stock market.

datay <- "FINRAMarginDebt_Log"
ylim <- c(5, 15)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Take a close look at recent activity

Sometimes it is more helpful to view year over year growth.

More near-term trend.

Take a look at some of the correlations

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

Comparison to the Russell 2000

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "RLG.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

OCC Options Volumes

See what is happening with the options volumes for equities. (From: https://www.theocc.com/webapps/historical-volume-query)

Looks like options on non-equity co-occurs with peaks/troughs?.

Market Volatility

Take a look at some of the indications of market volatility

CBOE VIX

As markets become complacent (low VIX) and high values, peaks often occur.

Compare the VIX to some of the ETF’s out there.

There

Not much predictive in VIX, take a quick look at the smoothed derivative.

S&P Daily Swings

Daily changes in the S&P should correlate well with the VIX.

More of a correlating series than a predictor.

Employment and payrolls

Unemployment rates

Unemployment rates will probably be useful, let’s take a look at the U-3. The data is a little noisy so there is also a smoothed version plotted. There seems to be a relationship between the unemployment rate and the recessions, but it could be a lagging indicator. This will be explored a little bit more later.

Suggested by Charlie and a Wealthian video the 12 month-MA might be helpful to look at.

Looking at the unemployment rate, the eye is drawn to the rise and fall of the data, this suggests that the derivative might be helpful as well. The figure below shows the results, using a Savitzky-Golay FIR filter. It looks like the unemployment rate peaks in the middel of the recession. That peak might be a good buy signal.

Continuing Claims

A good measure of how much unemployment is growing.

Continued claims, also referred to as insured unemployment, is the number of people who have already filed an initial claim and who have experienced a week of unemployment and then filed a continued claim to claim benefits for that week of unemployment. Continued claims data are based on the week of unemployment, not the week when the initial claim was filed

https://fred.stlouisfed.org/series/CCNSA

A good measure of how much unemployment is growing

Initial Claims

A good measure of how much unemployment is growing.

An initial claim is a claim filed by an unemployed individual after a separation from an employer. The claim requests a determination of basic eligibility for the Unemployment Insurance program.

https://fred.stlouisfed.org/series/ICSA

Unemployment rates, year-over-year

Both the headline unemployment and U-6 number changes are similar. During the upswing on the cycle it does look like the headline number falls faster than U-6

The second derivative of the unemployment rate does have zero crossings near the middle point of a recession. This would make it a helpful buy signal for the trading strategy.

Unemployment rates, similar periods

Historically the last two years of record low unemployment appear most similar to the 1971-1973 time frame. Just before inflation took off.

Unemployment rates, U-6 and headline number.

Let’s also take a look at the total unemployed, U-6. It continues to fall as the headline number stabilizes as people return to the work force. An indicator the cycle is beginning to top out.

Difference between U6 and U3 to see how close the economy is getting to full employment.

Unemployment and market bottoms

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Initial jobless claims

We will also take a look at initial jobless claims, this should start to rise just before the unemployment rate.

It looks like the jobless claim tend to peak more towards the end of the recession. It does not seem to be as strong of a sell indicator as the U-3 rate.

Jobless claims have a seasonal component to them. One way to reduce this effect is to calculate year over year growth. That helps some, the peaks seem to be more closely aligned with the middle to end of recessions.

Take a closer look at recent data

## Warning: Removed 1 rows containing missing values (geom_text).

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Take a look at the percentage of the population looking for work

A bit more recent trend

Unemployment Level

ADP data here. comes out before the official numbers.

Look at the year-over-year change in ADP.

ADP data divided by the population

Payrolls

Look at the BLS data on payrolls. Check the NSA series, then we will look at YoY data.

Hours worked

Sparked by an article at Mises (https://mises.org/wire/how-alexandria-ocasio-cortez-misunderstands-american-poverty), take a look at average weekly hours

The time series is pretty lumpy, plot the YoY change

A more recent look at average weekly hours of production

Industrial Production

Industrial production is also known to fall during an economic downturm, let’s take a look at some of the data from the FRED on industrial production. It does seem to peak prior to a recession so let’s smooth and look at the derivative as it might be a good indicator as well.

Industrial production over the last ten years or so

The derivative isn’t bad, but it sometimes crosses zeros well into a recession. That is less helpful as either a buy or sell indicator. A better measure might year over year (YoY) change.

The year over year change has a similar appearance. The low values at the beginning make the year over year values larger than the more recent values. Seems like it will rank low a reliable indicator.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 12)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 50)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail Sales

Retail sales, aggregate

Retail sales also change during recession. As the plot below shows, it seems to follow the trend of industrial production. It might be too strongly correlated to add much to the model. The will be examined in the correlation section.

The derivative of retail sales is a little more erratic than is was the industrial products. Looks like it might be helpful to include in the model as well.

Retail sales, aggregate year-over-year

Take a look at year-over-year changes

Retail sales and unemployment correlations

Let’s see how that looks on year over year basis. Interesting to compare to unemployment rates there appears to a correlation over the long term.

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## replace the existing scale.

There is some similarity. The rolling correlation shows the inverse relationship prior to a recession.

datay1 <- "RSALESAGG_YoY"
ylim1 <- c(-12.5, 12.5)

datay2 <- "UNEMPLOY_YoY"
ylim2 <- c(-30, 150)

dtStart <- as.Date("1jan1970","%d%b%Y")

w <- 180
corrName <- calcRollingCorr(dfRecession,df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail sales correlation and industrial production

Industrial production and retail sales look very similar so the plot below shows the 360 correlation. The corerlation does tend to fall around a recession, although 2008 was so bad that they both fell together. Not sure if it is that useful.

datay1 <- "INDPRO"
ylim1 <- c(40, 125)

datay2 <- "RSALESAGG"
ylim2 <- c(100000, 200000)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 60
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

It is interesting to see the strong correlation; however, I suspect this is due to more to the shape of the trends. How do the YoY correlations look? They are a little less correlated, probably better to use in the machine learning later.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 20)

datay2 <- "RSALESAGG_YoY"
ylim2 <- c(-20, 20)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Advance Retail Sales

This is an advanced estimate of the retail sales value.

Also take a look at year over year

Retail sales and the labor market

Income

Real Personal Income

Real Personal Income (Excluding Transfer, Annual)

During a recession real personal income falls. In the plot the peaks can be seen prior to each recession.

datay <- "W875RX1"
ylim <- c(3000, 15000)
plotSingleQuickModern(datay, ylim)

The features we are interested in are the peaks and valleys so we’ll use the derivative to get to those. Interesting, there is usually a first zero crossing before a recession and a second during or just after the recession.

Real personal income might have some seasonal variance, but it seems the year over year change tells the same story.

Price and cost measures

This section shows price and cost measures.

Two commonly used indexes are the CPI (consumer price index) and PPI (producer price index). CPI tries to show final prices paid for goods and services by urban U.S. consumers. This index includes sales tax and imports. The PPI attempts to reflect the prices paid at all stages of production, including goods and services purchases as inputs as well as goods and services purchased by consumers from retail and producer sellers. The PPI does not include imports or sales tax. The CPI reflects all rebates and financing plans wherease the PPI reflects only those rebate and financing plans provided by the producer. For example if an automotive manufacturer offers a rebate of $500 and the dealer offers an additional rebate of $500 then the PPI would reflect only the automotive manufacturer rebate, but the CPI would reflect both rebates.

Sources; https://www.bls.gov/opub/hom/pdf/cpihom.pdf and https://www.bls.gov/opub/hom/pdf/ppi-20111028.pdf.

Consumer price index

What does CPI look like?

datay <- "CPIAUCSL"
ylim <- c(0, 300)
plotSingleQuickModern(datay, ylim)

Check out the YoY growth

datay <- "CPIAUCSL_YoY"
ylim <- c(-2, 15)
plotSingleQuickModern(datay, ylim)

CPI to PPI

Suggested by Charlie, it can be helpful to look at the relationship between producer prices and consumer prices.

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Producer Price Index (Commodities)

Commodities

Basket

Take a look at some trends of baskets of commodities.

This plot examines commodity performance relative to the GDP deflator

Crude oil

Look at a trend of West Texas Intermediate (WTI)

This is ticker data from yahoo

Take a look at both WTI and Brent crude.

Real price of crude using producer price index for commodities

Gold

As risks increase investors often flock to safe haven assets like gold. An up-tick in prices can indicate investor uncertainty. This can be seen in the nominal price plot around 1980 and again in 2007.

This plots out the real price of gold by two different deflators. PPI corrected price is a little higher, to be expected since CPI also includes the effects of sales tax and imports. The spike in 1980 is especially pronounced in this series.

See how nominal and real prices look year over year. From the long-term view seems like there is little difference in the three series. Although not shown, even over the near-term there is little difference in the series.

See how gold correlates with the VIX. Both gold and VIX should respond to investor axiety, but it doesn’t look like it correlates very well.

Copper

Dr. Copper has a reputation as an indicator of economic malaise, but it does not seem to have much of a correlation with the recessions. The series below is from CME via Quandl. It has a lot of data so I am also looking at the smoothed version.

Copper is one of the commodities in the PPI so it is a bit of a proxy for how copper is doing relative to the basket of commodities.

The change in prices, year over year, do generally peak prior to a recession. The time and shape of this peak varies, but it still might be helpful. A couple of the large troughs do seem to correlate with the end of the recession. Likely this is because industrial production has also fallen.

There is some correlation between copper and the smooth recession initiator, especially at the end of the recession.

Might be easier to see correlation in a dot plot format.

This is a legacy series from FRED. It has not been updated in a couple of years so I am assuming it will go away.

Oil Services

Amazing events in the first half of 2020, take a look at those

See how the players are doing

Federal Reserve

The federal reserve has an impact on the economy, here are some data series relating to that.

Little bit closer

datay <- "WALCL"
ylim <- c(0, 10000)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Federal Reserve Reverse Repo Agreements

Compare liabilities to reverse repo trends

Take a look at more recent trends

Spiky, might be easier to look at year-over-year

Normalized by GDP

datay <- "WLRRAL.by.GDP"
ylim <- c(0, 4)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Overnight Bank Funding Rate

“The overnight bank funding rate is calculated using federal funds transactions and certain Eurodollar transactions. The federal funds market consists of domestic unsecured borrowings in U.S. dollars by depository institutions from other depository institutions and certain other entities, primarily government-sponsored enterprises, while the Eurodollar market consists of unsecured U.S. dollar deposits held at banks or bank branches outside of the United States. U.S.-based banks can also take Eurodollar deposits domestically through international banking facilities (IBFs). The overnight bank funding rate (OBFR) is calculated as a volume-weighted median of overnight federal funds transactions and Eurodollar transactions reported in the FR 2420 Report of Selected Money Market Rates. Volume-weighted median is the rate associated with transactions at the 50th percentile of transaction volume. Specifically, the volume-weighted median rate is calculated by ordering the transactions from lowest to highest rate, taking the cumulative sum of volumes of these transactions, and identifying the rate associated with the trades at the 50th percentile of dollar volume. The published rates are the volume-weighted median transacted rate, rounded to the nearest basis point.” https://www.newyorkfed.org/markets/obfrinfo.

Secured Overnight Financing Rate

“The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities. The SOFR includes all trades in the Broad General Collateral Rate plus bilateral Treasury repurchase agreement (repo) transactions cleared through the Delivery-versus-Payment (DVP) service offered by the Fixed Income Clearing Corporation (FICC), which is filtered to remove a portion of transactions considered “specials” " https://apps.newyorkfed.org/markets/autorates/sofr

Take a look at the variation (99th - 1st percentile)

Reserve Balances with Federal Reserve Banks

Hard to get a sense of these series in the absolute. Take a look relative to GDP.

By double entry book-keeping reserves+loans (assets) = deposit (liabilities). Does that really work?

Correlation Between Reserves and Total Loans

As reserves increase there should be less lending. That correlation generally holds.

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## replace the existing scale.

Did the reserve balances increase after the 2016 and 2018 drops? Not in the same way. There are some relationships between the equities market and the reserves though.

Explicitly correlate reserve balances and total loans. It is a weak and noisy correlation.

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 990 rows containing non-finite values (stat_smooth).

Interest on excess reserves

Monetary Base

Currency trend, base

This used to trend along with GDP. It doesn’t anymore.

Money supplies

Basic currency trend (currency component of M1)

datay <- "WCURRNS_YoY"
dtStart = as.Date('1980-01-01')
ylim <- c(0, 17)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

datay <- "WCURRNS_YoY"
dtStart = as.Date('2000-01-01')
ylim <- c(0, 20)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

The rate of change of money supply could be an indicator of a recession. Let’s see how that compares.

Intervention in the repo market

The federal reserve provides liquidity to the repo market, summary of that action

European central bank

The European central band (ECB) has taken a different path compared to the US Federal Reserve bank.

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Federal Debt

The government is a big driver of the economy, let’s see what it is doing in the debt markets.

datay <- "GFDEBTN"
ylim <- c(0, 35000000)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_Log"
ylim <- c(12, 18)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_YoY"
ylim <- c(-10, 25)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal debt as percent GDP

datay <- "GFDEGDQ188S"
ylim <- c(30, 150)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal deficit as percent GDP

datay <- "FYFSGDA188S"
ylim <- c(-30, 5)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Charlie Hatch has a nice format of deficit versus debt:

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Nonfinancial Corporate Business Debt

What about Nonfinancial corporate business and debt securities? Hopefully this doesn’t follow the business loan trends.

That is crazy steep. Time for a log format, see if that brings out the peaks and troughs. That’s a litte better, it looks like there might be a change in slope prior to the recessions.

The derivative doesn’t seem to be much help. There is not much correlation between the zero crossings and the NEBR recessions.

Debt cycle

This analysis roughly follows the ideas in Big Debt Crises book by Ray Dalio.

Total loans

One business cycle theory describes recessions as a market adjustment to mis-allocated assets, often fueled by an credit expansion. That makes the volume of loans an interesting feature to look at. In the presentation of data it looks like the great recession had the largest impact.

Plotting the year over year growth rate helps pull out those small changes in the early years in the data. Peaks can be seen prior to most recessions.

Zoom in to the last couple of decades

As long term interest rates rise, loans should start to tick down. To check this, the total loans and 10 to 1 year spreads are plotted. This is generally the trend observed.

There is a good correlation between these two variables. This next section plots that correction explicitly.

Total loans as percent of GDP

This is the total loans. I think the picture is too broad to point to a specific sector of the economy. The debt burden assumes interest rates are tied to the 10-year treasury: (TOTLNNSA * DGS10) / 100

Commercial and industral loans

Business loans should slow before the recession (a contraction in credit as rates rise).

Commercial and industrial loans as percent of GDP and and income

Look at business debt normalized by GDP over the entire time series. This ratio often peaks at the mid-point of a recession.

https://www.wsj.com/articles/this-isnt-your-fathers-corporate-bond-market-11590574555

“Bonds are behaving more like bank debt, which tends to remain stable or even increase at the onset of recessions, as lenders keep distressed clients afloat—and only later turn off the taps. This was confirmed by a recent report from the Bank for International Settlements. It also found a tight link between this lending cycle and the “real” economy’s booms and busts."

I assume that interest is related to the 10-year treasure: (TOTCINSA * DGS10) / 100

Farm loans

See how the farming sector is fairing.

Real estate loans

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

This gives a big picture, but makes it hard to connect the loans with the income needed to cover those loans. In the next section, loans will be broken up by commercial and residential.

Real Estate (Residential)

In absolute terms the mortgages have increased, but it does not appear to be out of line with the overall economy.

Normalized by GDP it is easier to see the peak in 2008 and that loan levels appear reasonable at the commercial banks. I updated this plot to include the estimated single-family home sales volume to give a sense of percentage of home sales that are cash.

Maybe the GSE’s are making loans. Take a look at the total mortgages from Z.1 as a percentage of GDP. That does not look too far off trend (ignoring that peak in 2008).

I am assuming that personal income is paying for the mortgages.

Real estate (residential) as percent of GDP and and income

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How do the number of starts compare to population?

Consumer loans

Focusing on the consumer sector the growth in debt and incomes can be directly compared. Personal income, as a percent of GDP, remains nearly constant. It is not uncommon for the personal income to rise prior to a recession. Likely this reflect increasing asset prices and market returns. Also interesting to see the loans pick up after interest rates dropped in 1982.

Consumer loans as percent of GDP and and income

Take a closer look since the 2008 recession. Looks like loans are starting to slow as the interest burden rises and incomes remain stable. There are some anomolies in the A065RC1A027NBEA data series because it only updates onces a year. the PI series updates once a month but is noisier and seasonally adjusted. It also shows incomes rising in the middle of the 2008 recession, which doesn’t seem to be accurate.

## Warning: Removed 1 rows containing missing values (geom_text).
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## Warning: Removed 1 rows containing missing values (geom_hline).

Repo market

This market went through some stress in 2008, it is happening again so setup some plots to watch it.

Nonfincial corporate business security repo asset level

Bonds

T-Bills and Yield Curve

Speaking of loans, interest rates also play into this. This analysis will focus on treasure bills. The 3-month is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 6.0)
dtStart = as.Date('2017-01-01')
p1 <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

# {r bond3monthlibor, echo=FALSE } # # datay <- "TB3MS" # datay_aux <- "USD1MTD156N" # ylim <- c(0, 12) # dtStart = as.Date('1985-01-01') # myPlot <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", # getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE) # myPlot <- myPlot + geom_line(data=df.data, aes_string(x="date", y=datay_aux, colour=shQuote(datay_aux)), na.rm = TRUE) # # myPlot # # Check out LIBOR and fed funds rate

The 1-year is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "DGS10"
datay.aux <- "TNX.Close"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Close in, the trend towards inversion be more easily seen. I am also comparing data from the CBOE as well as FRED.

Bond yields are a good proxy for interest rates. As rates rise the theory goes that loans should decrease (inverse correlation).

And a longer window

The yield curve (30 year bond rate minus the 10 year bond rate) may not be a good recession indicator, but a collapse is not good (https://blogs.wsj.com/moneybeat/2018/04/30/theres-more-than-one-part-of-the-yield-curve-getting-flatter/).

The yield curve (10 year bond rate minus the 1 year bond rate) seems to a good indicator of an oncoming recession. It could be a buy indicator by itself.

More recent data

Just the last 24 months or so.

Plot the 10 Year to 3 month over a few decades to see what the outling cases look like

The last two year compare favorably with the period around the 2015-2016 turndown, driven primarily by slowing of the Chinese GDP. Not a debt-driven cycle.

This plot format was suggested by a mises.org article (https://mises.org/wire/yield-curve-accordion-theory), but they only went back to 1988. The date seemed arbitrary so I went back further in time.

Take a look at more recent data

Try looking at a 1-year average of the above time series

High quality bonds

datay <- "AAA"
ylim <- c(1.5, 10)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds to 10-year treasury

High quality bonds long-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('1967-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds near-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('2007-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High yield spread

“This data represents the Option-Adjusted Spread (OAS) of the ICE BofAML US Corporate A Index, a subset of the ICE BofAML US Corporate Master Index tracking the performance of US dollar denominated investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a given investment grade rating A. The ICE BofAML OASs are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond‚Äôs OAS, weighted by market capitalization. When the last calendar day of the month takes place on the weekend, weekend observations will occur as a result of month ending accrued interest adjustments.”

• ICE Benchmark Administration Limited (IBA), ICE BofAML US Corporate A Option-Adjusted Spread [BAMLC0A3CA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BAMLC0A3CA, July 4, 2019.

datay <- "BAMLC0A3CA"
ylim <- c(0, 7)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Municipal bond market

Suggest by a WSJ article, change in volume for high-risk muni’s. Doesn’t look like there is much too it yet.

https://www.wsj.com/articles/risky-municipal-bonds-are-on-a-hot-streak-11558949401?mod=hp_lead_pos3

datay <- "HYMB.Close"
ylim <- c(40, 62)
dtStart = as.Date('2011-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

datay <- "HYMB.Volume"
ylim <- c(0, 1750000)
p1.vol <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


datay <- "GSPC.Open"
datay_aux <- "GSPC.Close"
ylim <- c(1500, d.GSPC.max )
p2 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


grid.arrange(p1,
             p1.vol,
             p2,
             ncol = 1,
             top = "High Yield Muni's and S&P Price")

Total Loans and yield curve correlation

This relationship was suggest by Charlie and it is an interesting one. As the yield curve flattens (10-year and 1-year rates converge), total loans grow. The generalization is not always accurate, but it does fit.

## `geom_smooth()` using formula 'y ~ x'

I wanted to see how this looked compared to the 3 month

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 282 rows containing non-finite values (stat_smooth).

Consumer loans and yield curve correlation

Compared to business loans, consumer loans seem to have to response to the 10Y to 3M yield curve.

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 311 rows containing non-finite values (stat_smooth).

Business loans and yield curve correlation

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 101 rows containing non-finite values (stat_smooth).

That’s pretty good correlation. Let’s see what the rolling correlation looks like.

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 720
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

One other items, let’s see how loans do versus the federal funds rate

## `geom_smooth()` using formula 'y ~ x'

Baker Hughes Rig Count

BEA Supplemental Estimates, Motor Vehicles

Definitions

Autos–all passenger cars, including station wagons.
Light trucks–trucks up to 14,000 pounds gross vehicle weight, including minivans and
sport utility vehicles. Prior to the 2003 Benchmark Revision light trucks were up to 10,000 pounds.
Heavy trucks–trucks more than 14,000 pounds gross vehicle weight.
Prior to the 2003 Benchmark Revision heavy trucks were more than 10,000 pounds.
Domestic sales–United States (U.S.) sales of vehicles assembled in the U.S., Canada, and Mexico.
Foreign sales–U.S. sales of vehicles produced elsewhere.
Domestic auto production–Autos assembled in the U.S.
Domestic auto inventories–U.S. inventories of vehicles assembled in the U.S., Canada, and Mexico.

TAble 6 - Light Vehicle and Total Vehicle Sales

Auto sales

A WSJ article suggested that auto sales might be a good indicator so bring that to the mix. It does have troughs that correlate with recessions

There might be some seasonal variance in the auto sales so lets take a look at the year over year. The data is pretty noisy, it probably will not make a very good indicator.

BEA Gross Domestic Product

Data in this section come from the Bureau of Economic Analysis.

Table 1.1.5. Gross Domestic Product

[Billions of dollars] Seasonally adjusted at annual rates

A191RC: Gross Domestic Product - Line 1

GDP numbers tend to lag so this series is truly an afterthought. But it does have some correlation with the recessions.

GDP does not reflect the capacity of the economy nor the efficiency. Shrinking capacity and lower prices at constant volumes would indicate improvements in effeciency/productivity which is good for the economy, but does not move the GDP upward.

Looks like the year over year change on the GDP should correlate well with unemployment.

Table 1.1.9. Implicit Price Deflators for Gross Domestic Product

[Index numbers, 2012=100] Seasonally adjusted

A191RD: Gross Domestic Product - Line 1

This is GDP price deflator series.

GDP normalized by CPI

Normalize GDP by CPI

Economic yield curve (GDP to 1-year treasury)

GDP versus the yield on the 1-year. This series was prompted by an article suggesting that the “economic yield curve” should be used to indicate a recession rather than an inverted yield curve. Less of indicator and more of concurrent confirmation of recession. Not sure why they would be related either.

Economic yield curve (GDP to 3-month treasury)

Same idea as above, but applied the 3-month treasury.This one has fewer false triggers, but is not as helpful as 10Y to 3M spread in predicting a recession.

A824RC: National defense Federal Gov’t Expenditures - Line 24

U.S. Bureau of Economic Analysis, Federal Government: National Defense Consumption Expenditures and Gross Investment [FDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FDEFX, April 6, 2021.

A825RC: Nondefense Federal Gov’t Expenditures - Line 25

U.S. Bureau of Economic Analysis, Federal Government: Nondefense Consumption Expenditures and Gross Investment [FNDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FNDEFX, April 6, 2021.

Table 6.16D. Corporate Profits by Industry

Select series from Table 6.16D

A051RC: Corporate profits with inventory and capital consumption adjustment

From BEA’s documentation (https://www.bea.gov/media/5671):

“BEA’s featured measure of corporate profits — profits from current production - provides a comprehensive and consistent economic measure of the income earned by all U.S. corporations. As such, it is unaffected by changes in tax laws, and it is adjusted for nonreported and misreported income. It excludes dividend income, capital gains and losses, and other financial flows and adjustments, such as deduction for “bad debt.” Thus, the NIPA measure of profits is a particularly useful analytical measure of the health of the corporate sector. For example, in contrast to other popular measures of corporate profits, the NIPA measure did not show the large run-up in profits during the late 1990s that was primarily attributable to capital gains.

Profits after tax with IVA and CCAdj is equal to corporate profits with IVA and CCAdj less taxes on corporate income. It provides an after-tax measure of profits from current production."

Data is Line 1 of Table 6.16D

A053RC: Corporate profits without inventory and capital consumption adjustment

Profits look a bit flat over the last several years in this series.

Table 2.6. Personal Income and Its Disposition, Monthly

Billions of dollars; months are seasonally adjusted at annual rates.

A065RC Personal Income - Line 1

BEA Account Code: A065RC

Personal income is the income that persons receive in return for their provision of labor, land, and capital used in current production and the net current transfer payments that they receive from business and from government.25 Personal income is equal to national income minus corporate profits with inventory valuation and capital consumption adjustments, taxes on production and imports less subsidies, contributions for government social insurance, net interest and miscellaneous payments on assets, business current transfer payments (net), current surplus of government enterprises, and wage accruals less disbursements, plus personal income receipts on assets and personal current transfer receipts. A Guide to the National Income and Product Accounts of the United States (NIPA) - (http://www.bea.gov/national/pdf/nipaguid.pdf)

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Income [PI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PI, July 11, 2019.

DPCERC: Personal consumption expenditures (PCE) - Table 2.1, Line 29

BEA Account Code: DPCERC Personal consumption expenditures (PCE) is the primary measure of consumer spending on goods and services in the U.S. economy. 1 It accounts for about two-thirds of domestic final spending, and thus it is the primary engine that drives future economic growth. PCE shows how much of the income earned by households is being spent on current consumption as opposed to how much is being saved for future consumption. -https://www.bea.gov/system/files/2019-12/Chapter-5.pdf

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures [PCE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCE, June 12, 2020

DPCERG: Personal consumption expenditures Price Index (PCEPI) - Table 2.1, Line 29

BEA Account Code: DPCERG The gross domestic product price index measures changes in prices paid for goods and services produced in the United States, including those exported to other countries. Prices of imports are excluded. The gross domestic product implicit price deflator, or GDP deflator, basically measures the same things and closely mirrors the GDP price index, although the two price measures are calculated differently. The GDP deflator is used by some firms to adjust payments in contracts.

The gross domestic purchases price index is BEA’s featured measure of inflation for the U.S. economy overall. It measures changes in prices paid by consumers, businesses, and governments in the United States, including the prices of the imports they buy.

BEA’s closely followed personal consumption expenditures price index, or PCE price index, is a narrower measure. It looks at the changing prices of goods and services purchased by consumers in the United States. It’s similar to the Bureau of Labor Statistics’ consumer price index for urban consumers. The two indexes, which have their own purposes and uses, are constructed differently, resulting in different inflation rates.

The PCE price index is known for capturing inflation (or deflation) across a wide range of consumer expenses and for reflecting changes in consumer behavior. For example, if the price of beef rises, shoppers may buy less beef and more chicken. Also, BEA revises previously published PCE data to reflect updated information or new methodology, providing consistency across decades of data that’s valuable for researchers. The PCE price index is used primarily for macroeconomic analysis and forecasting. -https://www.bea.gov/resources/learning-center/what-to-know-prices-inflation

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures: Chain-type Price Index [PCEPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCEPI, April 25, 2021.

A072RC: Personal Savings Rate - Line 35

Consumers tend to pull down their savings rates as unemployment decreases and market conditions improve. This series has tended to be unreliable due to the size of revisions during the comprehensive update carried out by the BEA. The last update on this series moved the rate from 4.2 to 6.7 percent.

(https://www.bloomberg.com/news/articles/2018-07-27/americans-have-been-saving-much-more-than-thought-new-data-show)

BEA Account Code: A072RC Personal saving as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate,” is calculated as the ratio of personal saving to DPI. Personal saving is equal to personal income less personal outlays and personal taxes; it may generally be viewed as the portion of personal income that is used either to provide funds to capital markets or to invest in real assets such as residences.(https://www.bea.gov/national/pdf/all-chapters.pdf) A Guide to the National Income and Product Accounts of the United States (NIPA).

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Saving Rate [PSAVERT], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PSAVERT, July 9, 2019.

Take a closer look at the last decade

The relationship between personal savings and unemployment (U-3) can be better visualized with a scatter plot

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 167 rows containing non-finite values (stat_smooth).

The fit does not explain most of what is in the plot. Lets take a look at the rolling correlation.

datay1 <- "UNRATE"
ylim1 <- c(2, 12)

datay2 <- "PSAVERT"
ylim2 <- c(0, 35)

dtStart <- as.Date("1jan1985","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Personal savings to household net worth

A relationship between personal savings and household networth can be seen in a scatter plot. This was suggested by a WSJ article (https://blogs.wsj.com/dailyshot/2018/02/23/the-daily-shot-reasons-for-declining-u-s-household-savings-rate/).

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 1186 rows containing non-finite values (stat_smooth).

U.S. Census Bureau

U.S. International Trade in Goods and Services (FT900)

U.S. Bureau of Economic Analysis and U.S. Census Bureau, U.S. Imports of Goods by Customs Basis from China [IMPCH], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/IMPCH, October 5, 2019.

New Houses Sold and For Sale by Stage of Construction and Median Number of Months on Sales Market

Read an article suggesting that housing sales and sales growth could be useful. FRED only has new home data so start there.

datay <- "HSN1FNSA"
ylim <- c(0, 200)
dtStart = as.Date('1964-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA"
ylim <- c(0, 600)
p2 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA.minus.HSN1FNSA"
ylim <- c(0, 600)
p3 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

grid.arrange(p1,
             p2,
             p3,
             ncol = 1,
             top = "New Housing Sales")

New housing yoy

New Privately-Owned Housing Units Authorized in Permit-Issuing Places

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Housing Starts: Total: New Privately Owned Housing Units Started [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, June 13, 2020.

Take a look at privately owned starts

New Privately-Owned Houses Sold and For Sale

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Median Sales Price of Houses Sold for the United States [MSPUS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSPUS, June 13, 2020.

Finally, take a look at starts times the median price

Durable Goods

Suggested Citation: U.S. Census Bureau, Manufacturers’ New Orders: Durable Goods [UMDMNO], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UMDMNO, April 26, 2021.

Durable goods, not seasonally adjusted, divided by GDP

Durable goods, seasonally adjusted, divided by GDP

Federal reserve board H.8: Assets and Liabilities of Commercial Banks in the United States

Page 4: Not Seasonally adjusted, billions of dollars

Commercial and industrial loans, all commercial banks - Line 10

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Commercial and Industrial Loans, All Commercial Banks [BUSLOANS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BUSLOANS, July 11, 2019.

Taking a look at the difference in SA and NSA series. Seasonal adjustments do vary, but do not seem to be related to recessions.

The raw series is just too steep for any kind of machine learnine. This needs to be converted to log scale.

That’s a little better, let’s see what the smoothed derivative looks like.

That is odd…looks like this doesn’t cross zero unless we are getting close to, or into, a recession. The year over year tells about the same story. Might be a good indication of the end of a recession.

Consumer loans, all commercial banks - Line 20

Suggested Citation: Board of Governors of the Federal Reserve System (US), Consumer Loans, All Commercial Banks [CONSUMERNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CONSUMERNSA, July 11, 2019.

That spike in consumer loans is due to

“April 9, 2010 (Last revised September 23, 2011): As of the week ending March 31, 2010, domestically chartered banks and foreign-related institutions had consolidated onto their balance sheets the following assets and liabilities of off-balance-sheet vehicles, owing to the adoption of FASB’s Financial Accounting Statements No. 166 (FAS 166),”Accounting for Transfers of Financial Assets," and No. 167 (FAS 167), “Amendments to FASB Interpretation No. 46(R).”

This included a consumer loans, credit cards and other revolving plans change of $321.9B. That was a lot of off-balance-sheet bank assets.

Deposits, All Commercial Banks, all commercial banks - Line 34

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Deposits, All Commercial Banks [DPSACBW027SBOG], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DPSACBW027SBOG, May 14, 2020.

Federal reserve board Z.1: Financial Accounts of the United States

From the FRED website (https://fred.stlouisfed.org/release?rid=52):

"The Financial Accounts (formerly known as the Flow of Funds accounts) are a set of financial accounts used to track the sources and uses of funds by sector. They are a component of a system of macroeconomic accounts including the National Income and Product accounts (NIPA) and balance of payments accounts, all of which serve as a comprehensive set of information on the economy’s performance.(1) Some important inferences that can be drawn from the Financial accounts are the financial strength of a given sector, new economic trends, changes in the composition of wealth, and development of new financial instruments over time.(1)

Sectors are compiled into three categories: households, nonfinancial businesses, and banks. The sources of funds for a sector are its internal funds (savings from income after consumption) and external funds (loans from banks and other financial intermediaries). (1) Funds for a given sector are used for its investments in physical and financial assets. Dividing sources and uses of funds into two categories helps the staff of the Federal Reserve System pay particular attention to external sources of funds and financial uses of funds.(2) One example is whether households are borrowing more from banks—or in other words, whether household debt is rising. Another example might be whether banks are using more of their funds to provide loans to consumers. Transactions within a sector are not shown in the accounts; however, transactions between sectors are.(2) Monitoring the external flows of funds provides insights into a sector’s health and the performance of the economy as a whole.

Data for the Financial accounts are compiled from a large number of reports and publications, including regulatory reports such as those submitted by banks, tax filings, and surveys conducted by the Federal Reserve System.(2) The Financial accounts are published quarterly as a set of tables in the Federal Reserve’s Z.1 statistical release.

1. Teplin, Albert M. “The U.S. Flow of Funds Accounts and Their Uses.” Federal Reserve Bulletin, July 2001; http://www.federalreserve.gov/pubs/bulletin/2001/0701lead.pdf.
2. Board of Governors of the Federal Reserve System. “Guide to the Flow of Funds Accounts.” 2000, http://www.federalreserve.gov/apps/fof/."

L.102 Nonfinancial Business

FL102051003.Q: Nonfinancial corporate business; security repurchase agreements; asset

Asset level of nonfinancial business security repo agreements. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL102051003&t=

L.214 Loans

FL894123005.Q: All sectors; total loans; liability

Sum of domestic financial sectors, all sectors, total mortgages, and households/non-profits. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL894123005&t=L.107&bc=L.107:FL793068005&suf=Q

FL793068005.Q: Domestic financial sectors; depository institution loans n.e.c.; asset

Sum of Monetary authority; depository institution loans n.e.c.; asset and Private depository institutions; depository institution loans n.e.c.; asset. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL793068005&t=L.214&suf=Q

FL893169005.Q: All sectors; other loans and advances; liability

Sum of finance, government, and chartered institutions asset levels. https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893169005&t=L.214&suf=Q

FL893065005.Q: All sectors; total mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065005&t=L.214&suf=Q

FL893065105.Q: All sectors; home mortgages; asset

https://www.federalreserve.gov/apps/fof/DisplayTable.aspx?t=L.214

FL893065405.Q: All sectors; multifamily residential mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065405&t=L.214&suf=Q

FL893065505.Q: All sectors; commercial mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065505&t=L.214&suf=Q

FL893065603.Q: All sectors; farm mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065603&t=L.214&suf=Q

FL153166000.Q: Households and nonprofit organizations; consumer credit; liability

federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL153166000&t=L.214&suf=Q

B.101 Balance Sheet of Households and Nonprofit Organizations

FL152000005.Q: Households and nonprofit organizations; total assets, Level

string.source ID: FL152000005.Q.

FL152090006.Q: Household Net Worth as Percentage of Disposable Personal Income

string.source ID: FL152090006.Q. Household networth tends to fall as a recession start.

Productivity Yield Curve

GDP versus productivity

Manufacturing output and employees

Not sure if these relates to a recession, but fascinating to see how output and employees change with time.

datay <- "OUTMS"
ylim <- c(60, 120)
dtStart = as.Date('1987-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "MANEMP"
ylim <- c(10000, 20000)
dtStart = as.Date('1948-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "PRS30006163"
ylim <- c(40, 120)
dtStart = as.Date('1986-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Shipping volumes might be helpful in determining state of the economy.

datay <- "FRGSHPUSM649NCIS"
ylim <- c(0.8, 1.4)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "FRGSHPUSM649NCIS_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Freight, loosely, moves inversely to the trade deficit.

datay <- "BOPGTB_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

World bank air transportation. Only updated annually so less usefull, but interesting reference to above.

# datay <- "WWDIWLDISAIRGOODMTK1"
# ylim <- c(0, 250000)
# dtStart = as.Date('1999-01-01')
# plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Gross private domestic investment

Spending most certainly tips down prior to a recession. The gross private domestic investment data series, plotted in log format below, show how private investment pulls back prior to recessions.

The change in direction is a little easier to see if the derivative is plotted, first YoY then the smoothed derivative

Velocity

Productivity

Frequency: Quarterly The Productivity and Costs release on August 7, 2003, will reflect the June 2003 benchmark revision to payroll employment. Since employment is now reported on a North American Industry Classification System (NAICS) basis, all of the historical data will be revised. Changes as a consequence of the move to NAICS should not be significant since this release carries data at high levels of aggregation.

Suggested Citation: U.S. Bureau of Labor Statistics, Nonfarm Business Sector: Labor Productivity (Output per Hour) for All Employed Persons [OPHNFB], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/OPHNFB, December 24, 2022.

Date range to match census data

PMI

Industrial Production

This is a look at manufacturing industrial production. The yoY change should be a leading indicator of unemployment.

Housing

Take a look at housing starts. These can drop as rates rise.

Frequency: Monthly

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, New Privately-Owned Housing Units Started: Total Units [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, December 24, 2022.

Housing starts, NSA

HOUST reports at annual rate, but HOUSTNSA just reports the monthly numbers. I scale up the NSA to the annual rate.

Units: Thousands of Units, Not Seasonally Adjusted

Frequency: Monthly

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, New Privately-Owned Housing Units Started: Total Units [HOUSTNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUSTNSA, December 24, 2022.

Case-schiller price index

Population data

Many of the economic series can be better understood if normalized by population. Basic population and worker data from FRED.

Population to GDP

Look at GDP divided by CPI per person. It flattens and even dips a little prior to a recession. Might be worth looking at the derivative of this series.

That is worth a closer look

datay1 <- "GDPBYCPIAUCSLBYPOPTHM_SmoothDer"
ylim1 <- c(-5, 5)

datay2 <- "RecInit_Smooth"
ylim2 <- c(0, 1)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Correlation Study

Detailed correlations are explored above. Before concluding, let’s take a look at some overall correlation values to see if anything pops out.

Commodities

As mentioned above, copper, year over year, has some correlation with the recession initiation. It could be useful.

GDP Series

GDP, normalized first by CPI and then by population, looks like it migh correlate inversely with the recession indicators

Financials

Let’s see where we are so far. The correlation plot confirms some of the speculation above. The S&P 500 (GSPC.Open) is well correlated with industrial production (INDPRO), business loans (BUSLOANS), total loans (TOTLNNSA) , and nonfinancial corporate business debt (NCBDBIQ027S).

In this case, I want and indicator that rises prior to a recession. It looks like the unemployment rate (UNRATE), real personal income (W875RX1), and the yield curve (DGS10TO1) are all inversely correlated with the recession initiation indicator.

I thought the modified recession initiation would be a harder match, but there are quite a few correlated variables. Lets take a look at some of those in more detail

Complete list of symbols

Since it is tedious to do this one at a time, all the symbols were entered into a data frame, loaded, and aggregated together in a single xts object.

This is the complete list of symbol names and sources used in the project.